Merge branch 'master' into pay-4195-replace-old-popover-component

Signed-off-by: James Gee <james@justec.io>
Signed-off-by: James Gee <1285296+geemanjs@users.noreply.github.com>

.github/workflows/storybook.yml

@@ -43,7 +43,7 @@ jobs:
           pnpm add --global wrangler
 
       - name: Deploy
-        uses: cloudflare/wrangler-action@da0e0dfe58b7a431659754fdf3f186c529afbe65
+        uses: cloudflare/wrangler-action@707f63750981584eb6abc365a50d441516fb04b8
         id: cloudflare_deployment
         with:
           apiToken: ${{ secrets.CLOUDFLARE_API_TOKEN }}

.github/workflows/sync-public-api-docs.yml

@@ -137,7 +137,7 @@ jobs:
         if: steps.verify_file.outputs.file_exists == 'true'
 
         # Pin v7.0.8
-        uses: peter-evans/create-pull-request@18e469570b1cf0dfc11d60ec121099f8ff3e617a
+        uses: peter-evans/create-pull-request@84ae59a2cdc2258d6fa0732dd66352dddae2a412
         with:
           token: ${{ steps.generate_token.outputs.token }}
 

.github/workflows/update-node-popularity.yml

@@ -56,5 +56,5 @@ jobs:
           branch: update-node-popularity
           base: master
           delete-branch: true
-          author: n8n Bot <191478365+n8n-bot@users.noreply.github.com>
-          committer: n8n Bot <191478365+n8n-bot@users.noreply.github.com>
+          author: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
+          committer: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

docker/images/runners/Dockerfile.distroless

@@ -172,7 +172,8 @@ ARG N8N_VERSION=snapshot
 ARG N8N_RELEASE_TYPE=dev
 
 ENV NODE_ENV=production \
-    N8N_RELEASE_TYPE=${N8N_RELEASE_TYPE}
+    N8N_RELEASE_TYPE=${N8N_RELEASE_TYPE} \
+    HOME=/home/runner
 
 # Copy everything from the prepared runtime filesystem
 COPY --from=runtime-prep --chown=root:root /runtime/ /

packages/@n8n/ai-workflow-builder.ee/evaluations/README.md

@@ -104,21 +104,29 @@ The Langsmith integration provides two key components:
 
 #### 6. Pairwise Evaluation
 
-Pairwise evaluation provides a simpler, criteria-based approach to workflow evaluation. Instead of using the complex multi-metric evaluation system, it evaluates workflows against a custom set of "do" and "don't" rules defined in the dataset.
+Pairwise evaluation provides a criteria-based approach to workflow evaluation with hierarchical scoring and multi-judge consensus. It evaluates workflows against a custom set of "do" and "don't" rules defined in the dataset.
 
 **Evaluator (`chains/pairwise-evaluator.ts`):**
 - Evaluates workflows against a checklist of criteria (dos and don'ts)
 - Uses an LLM to determine if each criterion passes or fails
 - Requires evidence-based justification for each decision
-- Calculates a simple pass/fail score (passes / total rules)
+- Returns `primaryPass` (true only if ALL criteria pass) and `diagnosticScore` (ratio of passes)
 
 **Runner (`langsmith/pairwise-runner.ts`):**
 - Generates workflows from prompts in the dataset
-- Applies pairwise evaluation to each generated workflow
-- Reports three metrics to Langsmith:
-  - `pairwise_score`: Overall score (0-1)
-  - `pairwise_passed_count`: Number of criteria passed
-  - `pairwise_failed_count`: Number of criteria violated
+- Runs multiple LLM judges in parallel for each evaluation (configurable via `--judges`)
+- Aggregates judge results using majority vote
+- Supports filtering by `notion_id` metadata for single-example runs
+- Reports five metrics to Langsmith:
+  - `pairwise_primary`: Majority vote result (0 or 1)
+  - `pairwise_diagnostic`: Average diagnostic score across judges
+  - `pairwise_judges_passed`: Count of judges that passed
+  - `pairwise_total_violations`: Sum of all violations
+  - `pairwise_total_passes`: Sum of all passes
+
+**Logger (`utils/logger.ts`):**
+- Simple evaluation logger with verbose mode support
+- Controls output verbosity via `--verbose` flag
 
 **Dataset Format:**
 The pairwise evaluation expects a Langsmith dataset with examples containing:
@@ -217,6 +225,9 @@ GENERATE_TEST_CASES=true pnpm eval
 
 # With custom concurrency
 EVALUATION_CONCURRENCY=10 pnpm eval
+
+# With feature flags enabled
+pnpm eval --multi-agent --template-examples
 ```
 
 ### Langsmith Evaluation
@@ -229,11 +240,59 @@ export LANGSMITH_DATASET_NAME=your_dataset_name
 
 # Run evaluation
 pnpm eval:langsmith
+
+# With feature flags enabled
+pnpm eval:langsmith --multi-agent
 ```
 
 ### Pairwise Evaluation
 
-Pairwise evaluation uses a dataset with custom do/don't criteria for each prompt.
+Pairwise evaluation uses a dataset with custom do/don't criteria for each prompt. It implements a hierarchical scoring system with multiple LLM judges per evaluation.
+
+#### CLI Options
+
+| Option | Description | Default |
+|--------|-------------|---------|
+| `--prompt <text>` | Run local evaluation with this prompt (no LangSmith required) | - |
+| `--dos <rules>` | Newline-separated "do" rules for local evaluation | - |
+| `--donts <rules>` | Newline-separated "don't" rules for local evaluation | - |
+| `--notion-id <id>` | Filter to a single example by its `notion_id` metadata | (all examples) |
+| `--max-examples <n>` | Limit number of examples to evaluate (useful for testing) | (no limit) |
+| `--repetitions <n>` | Number of times to repeat the entire evaluation | 1 |
+| `--generations <n>` | Number of workflow generations per prompt (for variance reduction) | 1 |
+| `--judges <n>` | Number of LLM judges per evaluation | 3 |
+| `--concurrency <n>` | Number of prompts to evaluate in parallel | 5 |
+| `--name <name>` | Custom experiment name in LangSmith | `pairwise-evals` |
+| `--output-dir <path>` | Save generated workflows and evaluation results to this directory | - |
+| `--verbose`, `-v` | Enable verbose logging (shows judge details, violations, etc.) | false |
+| `--multi-agent` | Enable multi-agent architecture (see [Feature Flags](#feature-flags)) | false |
+| `--template-examples` | Enable template-based examples (see [Feature Flags](#feature-flags)) | false |
+
+#### Local Mode (No LangSmith Required)
+
+Run a single pairwise evaluation locally without needing a LangSmith account:
+
+```bash
+# Basic local evaluation
+pnpm eval:pairwise --prompt "Create a workflow that sends Slack messages" --dos "Use Slack node"
+
+# With don'ts and multiple judges
+pnpm eval:pairwise \
+  --prompt "Create a workflow that fetches data from an API" \
+  --dos "Use HTTP Request node\nHandle errors" \
+  --donts "Don't hardcode URLs" \
+  --judges 5 \
+  --verbose
+```
+
+Local mode is useful for:
+- Testing prompts before adding them to a dataset
+- Quick iteration on evaluation criteria
+- Running evaluations without LangSmith setup
+
+#### LangSmith Mode
+
+For dataset-based evaluation with experiment tracking:
 
 ```bash
 # Set required environment variables
@@ -242,14 +301,104 @@ export LANGSMITH_API_KEY=your_api_key
 # Run pairwise evaluation (uses default dataset: notion-pairwise-workflows)
 pnpm eval:pairwise
 
+# Run a single example by notion_id
+pnpm eval:pairwise --notion-id 30d29454-b397-4a35-8e0b-74a2302fa81a
+
+# Run with 3 repetitions and 5 judges, custom experiment name
+pnpm eval:pairwise --repetitions 3 --judges 5 --name "my-experiment"
+
+# Enable verbose logging to see all judge details
+pnpm eval:pairwise --notion-id abc123 --verbose
+
 # Use a custom dataset
 LANGSMITH_DATASET_NAME=my-pairwise-dataset pnpm eval:pairwise
 
 # Limit to specific number of examples (useful for testing)
-EVAL_MAX_EXAMPLES=2 pnpm eval:pairwise
+pnpm eval:pairwise --max-examples 2
+```
 
-# Run with multiple repetitions
-pnpm eval:pairwise --repetitions 3
+#### Multi-Generation Evaluation
+
+The `--generations` flag enables multiple workflow generations per prompt, providing a **Generation Correctness** metric:
+
+```bash
+# Run 3 generations per prompt with 3 judges each
+pnpm eval:pairwise --generations 3 --judges 3 --verbose
+
+# Example output:
+# Gen 1: 2/3 judges → ✓ PASS (diag=85%)
+# Gen 2: 1/3 judges → ✗ FAIL (diag=60%)
+# Gen 3: 3/3 judges → ✓ PASS (diag=95%)
+# 📊 [#1] 2/3 gens → PASS (gen_corr=0.67, diag=80%)
+```
+
+**Generation Correctness** = (# passing generations) / total generations:
+- With `--generations 3`: Values are 0, 0.33, 0.67, or 1
+- With `--generations 5`: Values are 0, 0.2, 0.4, 0.6, 0.8, or 1
+
+#### Hierarchical Scoring System
+
+The pairwise evaluation uses a multi-level scoring hierarchy:
+
+| Level | Primary Score | Secondary Score |
+|-------|--------------|-----------------|
+| Individual do/don't | Binary (true/false) | 0 or 1 |
+| 1 LLM judge | false if ANY criterion fails | Average of criteria scores |
+| N judges on 1 generation | Majority vote (≥50% pass) | Average diagnostic across judges |
+| N generations on 1 prompt | (# passing gens) / N | Average diagnostic across generations |
+| Full dataset | Average across prompts | Average diagnostic across all |
+
+This approach reduces variance from LLM non-determinism by using multiple judges and generations.
+
+#### Saving Artifacts with --output-dir
+
+The `--output-dir` flag saves all generated workflows and evaluation results to disk:
+
+```bash
+# Save artifacts to ./eval-output directory
+pnpm eval:pairwise --generations 3 --output-dir ./eval-output --verbose
+```
+
+**Output structure:**
+```
+eval-output/
+├── prompt-1/
+│   ├── prompt.txt              # Original prompt text
+│   ├── criteria.json           # dos/donts criteria
+│   ├── gen-1/
+│   │   ├── workflow.json       # Importable n8n workflow
+│   │   └── evaluation.json     # Judge results for this generation
+│   ├── gen-2/
+│   │   ├── workflow.json
+│   │   └── evaluation.json
+│   └── gen-3/
+│       ├── workflow.json
+│       └── evaluation.json
+├── prompt-2/
+│   └── ...
+└── summary.json                # Overall results summary
+```
+
+**workflow.json**: Directly importable into n8n (File → Import from file)
+
+**evaluation.json**: Contains per-judge results including violations and passes:
+```json
+{
+  "generationIndex": 1,
+  "majorityPass": false,
+  "primaryPasses": 1,
+  "numJudges": 3,
+  "diagnosticScore": 0.35,
+  "judges": [
+    {
+      "judgeIndex": 1,
+      "primaryPass": false,
+      "diagnosticScore": 0.30,
+      "violations": [{"rule": "...", "justification": "..."}],
+      "passes": [{"rule": "...", "justification": "..."}]
+    }
+  ]
+}
 ```
 
 ## Configuration
@@ -282,10 +431,77 @@ The evaluation will fail with a clear error message if `nodes.json` is missing.
 - `USE_LANGSMITH_EVAL` - Set to "true" to use Langsmith mode
 - `USE_PAIRWISE_EVAL` - Set to "true" to use pairwise evaluation mode
 - `LANGSMITH_DATASET_NAME` - Override default dataset name
-- `EVAL_MAX_EXAMPLES` - Limit number of examples to evaluate (useful for testing)
 - `EVALUATION_CONCURRENCY` - Number of parallel test executions (default: 5)
 - `GENERATE_TEST_CASES` - Set to "true" to generate additional test cases
 - `LLM_MODEL` - Model identifier for metadata tracking
+- `EVAL_FEATURE_MULTI_AGENT` - Set to "true" to enable multi-agent mode
+- `EVAL_FEATURE_TEMPLATE_EXAMPLES` - Set to "true" to enable template examples
+
+### Feature Flags
+
+Feature flags control experimental or optional behaviors in the AI Workflow Builder agent during evaluations. They can be set via environment variables or CLI arguments.
+
+#### Available Flags
+
+| Flag | Description | Default |
+|------|-------------|---------|
+| `multiAgent` | Enables multi-agent architecture with specialized sub-agents (supervisor, builder, configurator, discovery) | `false` |
+| `templateExamples` | Enables template-based examples in agent prompts | `false` |
+
+#### Setting Feature Flags
+
+**Via Environment Variables:**
+```bash
+# Enable multi-agent mode
+EVAL_FEATURE_MULTI_AGENT=true pnpm eval
+
+# Enable template examples
+EVAL_FEATURE_TEMPLATE_EXAMPLES=true pnpm eval:pairwise
+
+# Enable both
+EVAL_FEATURE_MULTI_AGENT=true EVAL_FEATURE_TEMPLATE_EXAMPLES=true pnpm eval:langsmith
+```
+
+**Via CLI Arguments:**
+```bash
+# Enable multi-agent mode
+pnpm eval --multi-agent
+
+# Enable template examples
+pnpm eval:pairwise --template-examples
+
+# Enable both
+pnpm eval:langsmith --multi-agent --template-examples
+```
+
+#### Usage Across Evaluation Modes
+
+Feature flags work consistently across all evaluation modes:
+
+**CLI Evaluation:**
+```bash
+pnpm eval --multi-agent --template-examples
+```
+
+**Langsmith Evaluation:**
+```bash
+pnpm eval:langsmith --multi-agent
+```
+
+**Pairwise Evaluation (LangSmith mode):**
+```bash
+pnpm eval:pairwise --multi-agent --template-examples
+```
+
+**Pairwise Evaluation (Local mode):**
+```bash
+pnpm eval:pairwise --prompt "Create a Slack workflow" --dos "Use Slack node" --multi-agent
+```
+
+When feature flags are enabled, they are logged at the start of the evaluation:
+```
+➔ Feature flags enabled: multiAgent, templateExamples
+```
 
 ## Output
 
@@ -304,14 +520,22 @@ The evaluation will fail with a clear error message if `nodes.json` is missing.
 ### Pairwise Evaluation Output
 
 - Results are stored in Langsmith dashboard
-- Experiment name format: `pairwise-evals-[uuid]`
-- Metrics reported:
-  - `pairwise_score`: Overall pass rate (0-1)
-  - `pairwise_passed_count`: Number of criteria that passed
-  - `pairwise_failed_count`: Number of criteria that were violated
+- Experiment name format: `<name>-[uuid]` (default: `pairwise-evals-[uuid]`)
+- Metrics reported (single generation mode):
+  - `pairwise_primary`: Binary pass/fail based on majority vote (0 or 1)
+  - `pairwise_diagnostic`: Average diagnostic score across judges (0-1)
+  - `pairwise_judges_passed`: Number of judges that returned primaryPass=true
+  - `pairwise_total_violations`: Sum of violations across all judges
+  - `pairwise_total_passes`: Sum of passes across all judges
+- Additional metrics reported (multi-generation mode with `--generations N`):
+  - `pairwise_generation_correctness`: (# passing generations) / N (0, 0.33, 0.67, 1 for N=3)
+  - `pairwise_aggregated_diagnostic`: Average diagnostic score across all generations
+  - `pairwise_generations_passed`: Count of generations that passed majority vote
+  - `pairwise_total_judge_calls`: Total judge invocations (generations × judges)
 - Each result includes detailed comments with:
-  - List of violations with justifications
-  - List of passes with justifications
+  - Majority vote summary
+  - List of violations with justifications (per judge)
+  - List of passes (per judge)
 
 ## Adding New Test Cases
 

packages/@n8n/ai-workflow-builder.ee/evaluations/chains/pairwise-evaluator.test.ts

@@ -52,7 +52,8 @@ describe('evaluateWorkflowPairwise', () => {
 
 		expect(result).toEqual({
 			...mockResult,
-			score: 1,
+			primaryPass: true,
+			diagnosticScore: 1,
 		});
 		expect(baseEvaluator.createEvaluatorChain).toHaveBeenCalledWith(
 			mockLlm,
@@ -69,7 +70,7 @@ describe('evaluateWorkflowPairwise', () => {
 		);
 	});
 
-	it('should calculate score correctly with violations', async () => {
+	it('should calculate diagnosticScore correctly with violations', async () => {
 		const mockResult = {
 			violations: [{ rule: "Don't do that", justification: 'Did it' }],
 			passes: [{ rule: 'Do this', justification: 'Done' }],
@@ -79,10 +80,11 @@ describe('evaluateWorkflowPairwise', () => {
 
 		const result = await evaluateWorkflowPairwise(mockLlm, input);
 
-		expect(result.score).toBe(0.5);
+		expect(result.primaryPass).toBe(false);
+		expect(result.diagnosticScore).toBe(0.5);
 	});
 
-	it('should return score 0 when no rules evaluated', async () => {
+	it('should return diagnosticScore 0 when no rules evaluated', async () => {
 		const mockResult = {
 			violations: [],
 			passes: [],
@@ -92,6 +94,7 @@ describe('evaluateWorkflowPairwise', () => {
 
 		const result = await evaluateWorkflowPairwise(mockLlm, input);
 
-		expect(result.score).toBe(0);
+		expect(result.primaryPass).toBe(true);
+		expect(result.diagnosticScore).toBe(0);
 	});
 });

packages/@n8n/ai-workflow-builder.ee/evaluations/chains/pairwise-evaluator.ts

@@ -32,7 +32,10 @@ const pairwiseEvaluationLLMResultSchema = z.object({
 });
 
 export type PairwiseEvaluationResult = z.infer<typeof pairwiseEvaluationLLMResultSchema> & {
-	score: number;
+	/** True only if ALL criteria passed (no violations) */
+	primaryPass: boolean;
+	/** Ratio of passed criteria to total criteria (0-1) */
+	diagnosticScore: number;
 };
 
 const EVALUATOR_SYSTEM_PROMPT = `You are an expert n8n workflow auditor. Your task is to strictly evaluate a candidate workflow against a provided set of requirements.
@@ -96,10 +99,12 @@ export async function evaluateWorkflowPairwise(
 	});
 
 	const totalRules = result.passes.length + result.violations.length;
-	const score = totalRules > 0 ? result.passes.length / totalRules : 0;
+	const diagnosticScore = totalRules > 0 ? result.passes.length / totalRules : 0;
+	const primaryPass = result.violations.length === 0;
 
 	return {
 		...result,
-		score,
+		primaryPass,
+		diagnosticScore,
 	};
 }

packages/@n8n/ai-workflow-builder.ee/evaluations/cli/runner.ts

@@ -2,6 +2,7 @@ import pLimit from 'p-limit';
 import pc from 'picocolors';
 
 import { createProgressBar, updateProgress, displayResults, displayError } from './display.js';
+import type { BuilderFeatureFlags } from '../../src/workflow-builder-agent.js';
 import { basicTestCases, generateTestCases } from '../chains/test-case-generator.js';
 import {
 	setupTestEnvironment,
@@ -25,6 +26,7 @@ type CliEvaluationOptions = {
 	testCaseFilter?: string; // Optional test case ID to run only a specific test
 	testCases?: TestCase[]; // Optional array of test cases to run (if not provided, uses defaults and generation)
 	repetitions?: number; // Number of times to run each test (e.g. for cache warming analysis)
+	featureFlags?: BuilderFeatureFlags; // Optional feature flags to pass to the agent (e.g. templateExamples, multiAgent)
 };
 
 /**
@@ -32,12 +34,20 @@ type CliEvaluationOptions = {
  * Supports concurrency control via EVALUATION_CONCURRENCY environment variable
  */
 export async function runCliEvaluation(options: CliEvaluationOptions = {}): Promise<void> {
-	const { repetitions = 1, testCaseFilter } = options;
+	const { repetitions = 1, testCaseFilter, featureFlags } = options;
 
 	console.log(formatHeader('AI Workflow Builder Full Evaluation', 70));
 	if (repetitions > 1) {
 		console.log(pc.yellow(`➔ Each test will be run ${repetitions} times for cache analysis`));
 	}
+	if (featureFlags) {
+		const enabledFlags = Object.entries(featureFlags)
+			.filter(([, v]) => v === true)
+			.map(([k]) => k);
+		if (enabledFlags.length > 0) {
+			console.log(pc.green(`➔ Feature flags enabled: ${enabledFlags.join(', ')}`));
+		}
+	}
 	console.log();
 	try {
 		// Setup test environment
@@ -105,7 +115,9 @@ export async function runCliEvaluation(options: CliEvaluationOptions = {}): Prom
 
 						// Create a dedicated agent for this test to avoid state conflicts
 						const testAgent = createAgent(parsedNodeTypes, llm, tracer);
-						const result = await runSingleTest(testAgent, llm, testCase, parsedNodeTypes);
+						const result = await runSingleTest(testAgent, llm, testCase, parsedNodeTypes, {
+							featureFlags,
+						});
 
 						testResults[testCase.id] = result.error ? 'fail' : 'pass';
 						completed++;

packages/@n8n/ai-workflow-builder.ee/evaluations/core/environment.ts

@@ -5,6 +5,7 @@ import { Client } from 'langsmith/client';
 import type { INodeTypeDescription } from 'n8n-workflow';
 
 import { anthropicClaudeSonnet45 } from '../../src/llm-config.js';
+import type { BuilderFeatureFlags } from '../../src/workflow-builder-agent.js';
 import { WorkflowBuilderAgent } from '../../src/workflow-builder-agent.js';
 import { loadNodesFromFile } from '../load-nodes.js';
 
@@ -76,12 +77,14 @@ export async function setupTestEnvironment(): Promise<TestEnvironment> {
  * @param parsedNodeTypes - Array of parsed node type descriptions
  * @param llm - Language model instance
  * @param tracer - Optional LangChain tracer
+ * @param featureFlags - Optional feature flags
  * @returns Configured WorkflowBuilderAgent
  */
 export function createAgent(
 	parsedNodeTypes: INodeTypeDescription[],
 	llm: BaseChatModel,
 	tracer?: LangChainTracer,
+	featureFlags?: BuilderFeatureFlags,
 ): WorkflowBuilderAgent {
 	return new WorkflowBuilderAgent({
 		parsedNodeTypes,
@@ -89,6 +92,7 @@ export function createAgent(
 		llmComplexTask: llm,
 		checkpointer: new MemorySaver(),
 		tracer,
+		featureFlags,
 	});
 }
 

packages/@n8n/ai-workflow-builder.ee/evaluations/core/test-runner.ts

@@ -1,7 +1,7 @@
 import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import type { INodeTypeDescription } from 'n8n-workflow';
 
-import type { WorkflowBuilderAgent } from '../../src/workflow-builder-agent';
+import type { BuilderFeatureFlags, WorkflowBuilderAgent } from '../../src/workflow-builder-agent';
 import { evaluateWorkflow } from '../chains/workflow-evaluator';
 import { programmaticEvaluation } from '../programmatic/programmatic-evaluation';
 import type { EvaluationInput, TestCase } from '../types/evaluation';
@@ -69,12 +69,22 @@ export function createErrorResult(testCase: TestCase, error: unknown): TestResul
 	};
 }
 
+export interface RunSingleTestOptions {
+	agent: WorkflowBuilderAgent;
+	llm: BaseChatModel;
+	testCase: TestCase;
+	nodeTypes: INodeTypeDescription[];
+	userId?: string;
+	featureFlags?: BuilderFeatureFlags;
+}
+
 /**
  * Runs a single test case by generating a workflow and evaluating it
  * @param agent - The workflow builder agent to use
  * @param llm - Language model for evaluation
  * @param testCase - Test case to execute
- * @param userId - User ID for the session
+ * @param nodeTypes - Array of node type descriptions
+ * @params opts - userId, User ID for the session and featureFlags, Optional feature flags to pass to the agent
  * @returns Test result with generated workflow and evaluation
  */
 export async function runSingleTest(
@@ -82,12 +92,15 @@ export async function runSingleTest(
 	llm: BaseChatModel,
 	testCase: TestCase,
 	nodeTypes: INodeTypeDescription[],
-	userId: string = 'test-user',
+	opts?: { userId?: string; featureFlags?: BuilderFeatureFlags },
 ): Promise<TestResult> {
+	const userId = opts?.userId ?? 'test-user';
 	try {
 		// Generate workflow
 		const startTime = Date.now();
-		await consumeGenerator(agent.chat(getChatPayload(testCase.prompt, testCase.id), userId));
+		await consumeGenerator(
+			agent.chat(getChatPayload(testCase.prompt, testCase.id, opts?.featureFlags), userId),
+		);
 		const generationTime = Date.now() - startTime;
 
 		// Get generated workflow with validation

packages/@n8n/ai-workflow-builder.ee/evaluations/index.ts

@@ -1,15 +1,54 @@
+import type { BuilderFeatureFlags } from '@/workflow-builder-agent';
+
 import { runCliEvaluation } from './cli/runner.js';
-import { runPairwiseLangsmithEvaluation } from './langsmith/pairwise-runner.js';
+import {
+	runLocalPairwiseEvaluation,
+	runPairwiseLangsmithEvaluation,
+} from './langsmith/pairwise-runner.js';
 import { runLangsmithEvaluation } from './langsmith/runner.js';
 import { loadTestCasesFromCsv } from './utils/csv-prompt-loader.js';
 
 // Re-export for external use if needed
 export { runCliEvaluation } from './cli/runner.js';
 export { runLangsmithEvaluation } from './langsmith/runner.js';
-export { runPairwiseLangsmithEvaluation } from './langsmith/pairwise-runner.js';
+export {
+	runLocalPairwiseEvaluation,
+	runPairwiseLangsmithEvaluation,
+} from './langsmith/pairwise-runner.js';
 export { runSingleTest } from './core/test-runner.js';
 export { setupTestEnvironment, createAgent } from './core/environment.js';
 
+/** Parse an integer flag with default value */
+function getIntFlag(flag: string, defaultValue: number, max?: number): number {
+	const arg = getFlagValue(flag);
+	if (!arg) return defaultValue;
+	const parsed = parseInt(arg, 10);
+	if (Number.isNaN(parsed) || parsed < 1) return defaultValue;
+	return max ? Math.min(parsed, max) : parsed;
+}
+
+/** Parse all CLI arguments */
+function parseCliArgs() {
+	return {
+		testCaseId: process.argv.includes('--test-case')
+			? process.argv[process.argv.indexOf('--test-case') + 1]
+			: undefined,
+		promptsCsvPath: getFlagValue('--prompts-csv') ?? process.env.PROMPTS_CSV_FILE,
+		repetitions: getIntFlag('--repetitions', 1),
+		notionId: getFlagValue('--notion-id'),
+		numJudges: getIntFlag('--judges', 3),
+		numGenerations: getIntFlag('--generations', 1, 10),
+		concurrency: getIntFlag('--concurrency', 5),
+		maxExamples: getIntFlag('--max-examples', 0), // 0 means no limit
+		verbose: process.argv.includes('--verbose') || process.argv.includes('-v'),
+		experimentName: getFlagValue('--name'),
+		outputDir: getFlagValue('--output-dir'),
+		prompt: getFlagValue('--prompt'),
+		dos: getFlagValue('--dos'),
+		donts: getFlagValue('--donts'),
+	};
+}
+
 /**
  * Main entry point for evaluation
  * Determines which evaluation mode to run based on environment variables
@@ -17,32 +56,54 @@ export { setupTestEnvironment, createAgent } from './core/environment.js';
 async function main(): Promise<void> {
 	const useLangsmith = process.env.USE_LANGSMITH_EVAL === 'true';
 	const usePairwiseEval = process.env.USE_PAIRWISE_EVAL === 'true';
+	const args = parseCliArgs();
 
-	// Parse command line arguments for single test case
-	const testCaseId = process.argv.includes('--test-case')
-		? process.argv[process.argv.indexOf('--test-case') + 1]
-		: undefined;
-
-	// Parse command line argument for CSV prompts file path
-	const promptsCsvPath = getFlagValue('--prompts-csv') ?? process.env.PROMPTS_CSV_FILE;
-
-	if (promptsCsvPath && (useLangsmith || usePairwiseEval)) {
+	if (args.promptsCsvPath && (useLangsmith || usePairwiseEval)) {
 		console.warn('CSV-driven evaluations are only supported in CLI mode. Ignoring --prompts-csv.');
 	}
 
-	// Parse command line arguments for a number of repetitions (applies to both modes)
-	const repetitionsArg = process.argv.includes('--repetitions')
-		? parseInt(process.argv[process.argv.indexOf('--repetitions') + 1], 10)
-		: 1;
-	const repetitions = Number.isNaN(repetitionsArg) ? 1 : repetitionsArg;
+	// Parse feature flags from environment variables or CLI arguments
+	const featureFlags = parseFeatureFlags();
 
 	if (usePairwiseEval) {
-		await runPairwiseLangsmithEvaluation(repetitions);
+		if (args.prompt) {
+			// Local mode - run single evaluation without LangSmith
+			await runLocalPairwiseEvaluation({
+				prompt: args.prompt,
+				criteria: { dos: args.dos ?? '', donts: args.donts ?? '' },
+				numJudges: args.numJudges,
+				numGenerations: args.numGenerations,
+				verbose: args.verbose,
+				outputDir: args.outputDir,
+				featureFlags,
+			});
+		} else {
+			// LangSmith mode
+			await runPairwiseLangsmithEvaluation({
+				repetitions: args.repetitions,
+				notionId: args.notionId,
+				numJudges: args.numJudges,
+				numGenerations: args.numGenerations,
+				verbose: args.verbose,
+				experimentName: args.experimentName,
+				outputDir: args.outputDir,
+				concurrency: args.concurrency,
+				maxExamples: args.maxExamples || undefined,
+				featureFlags,
+			});
+		}
 	} else if (useLangsmith) {
-		await runLangsmithEvaluation(repetitions);
+		await runLangsmithEvaluation(args.repetitions, featureFlags);
 	} else {
-		const csvTestCases = promptsCsvPath ? loadTestCasesFromCsv(promptsCsvPath) : undefined;
-		await runCliEvaluation({ testCases: csvTestCases, testCaseFilter: testCaseId, repetitions });
+		const csvTestCases = args.promptsCsvPath
+			? loadTestCasesFromCsv(args.promptsCsvPath)
+			: undefined;
+		await runCliEvaluation({
+			testCases: csvTestCases,
+			testCaseFilter: args.testCaseId,
+			repetitions: args.repetitions,
+			featureFlags,
+		});
 	}
 }
 
@@ -68,6 +129,36 @@ function getFlagValue(flag: string): string | undefined {
 	return undefined;
 }
 
+/**
+ * Parse feature flags from environment variables or CLI arguments.
+ * Environment variables:
+ *   - EVAL_FEATURE_TEMPLATE_EXAMPLES=true - Enable template examples feature
+ *   - EVAL_FEATURE_MULTI_AGENT=true - Enable multi-agent feature
+ * CLI arguments:
+ *   - --template-examples - Enable template examples feature
+ *   - --multi-agent - Enable multi-agent feature
+ */
+function parseFeatureFlags(): BuilderFeatureFlags | undefined {
+	const templateExamplesFromEnv = process.env.EVAL_FEATURE_TEMPLATE_EXAMPLES === 'true';
+	const multiAgentFromEnv = process.env.EVAL_FEATURE_MULTI_AGENT === 'true';
+
+	const templateExamplesFromCli = process.argv.includes('--template-examples');
+	const multiAgentFromCli = process.argv.includes('--multi-agent');
+
+	const templateExamples = templateExamplesFromEnv || templateExamplesFromCli;
+	const multiAgent = multiAgentFromEnv || multiAgentFromCli;
+
+	// Only return feature flags object if at least one flag is set
+	if (templateExamples || multiAgent) {
+		return {
+			templateExamples: templateExamples || undefined,
+			multiAgent: multiAgent || undefined,
+		};
+	}
+
+	return undefined;
+}
+
 // Run if called directly
 if (require.main === module) {
 	main().catch(console.error);

packages/@n8n/ai-workflow-builder.ee/evaluations/langsmith/runner.ts

@@ -5,6 +5,7 @@ import type { INodeTypeDescription } from 'n8n-workflow';
 import pc from 'picocolors';
 
 import { createLangsmithEvaluator } from './evaluator';
+import type { BuilderFeatureFlags } from '../../src/workflow-builder-agent';
 import type { WorkflowState } from '../../src/workflow-state';
 import { setupTestEnvironment, createAgent } from '../core/environment';
 import {
@@ -20,12 +21,14 @@ import { consumeGenerator, formatHeader, getChatPayload } from '../utils/evaluat
  * @param parsedNodeTypes - Node types
  * @param llm - Language model
  * @param tracer - Optional tracer
+ * @param featureFlags - Optional feature flags to pass to the agent
  * @returns Function that generates workflows from inputs
  */
 function createWorkflowGenerator(
 	parsedNodeTypes: INodeTypeDescription[],
 	llm: BaseChatModel,
 	tracer?: LangChainTracer,
+	featureFlags?: BuilderFeatureFlags,
 ) {
 	return async (inputs: typeof WorkflowState.State) => {
 		// Generate a unique ID for this evaluation run
@@ -43,7 +46,7 @@ function createWorkflowGenerator(
 		// Create agent for this run
 		const agent = createAgent(parsedNodeTypes, llm, tracer);
 		await consumeGenerator(
-			agent.chat(getChatPayload(messageContent, runId), 'langsmith-eval-user'),
+			agent.chat(getChatPayload(messageContent, runId, featureFlags), 'langsmith-eval-user'),
 		);
 
 		// Get generated workflow with validation
@@ -75,12 +78,24 @@ function createWorkflowGenerator(
 /**
  * Runs evaluation using Langsmith
  * @param repetitions - Number of times to run each example (default: 1)
+ * @param featureFlags - Optional feature flags to pass to the agent
  */
-export async function runLangsmithEvaluation(repetitions: number = 1): Promise<void> {
+export async function runLangsmithEvaluation(
+	repetitions: number = 1,
+	featureFlags?: BuilderFeatureFlags,
+): Promise<void> {
 	console.log(formatHeader('AI Workflow Builder Langsmith Evaluation', 70));
 	if (repetitions > 1) {
 		console.log(pc.yellow(`➔ Each example will be run ${repetitions} times`));
 	}
+	if (featureFlags) {
+		const enabledFlags = Object.entries(featureFlags)
+			.filter(([, v]) => v === true)
+			.map(([k]) => k);
+		if (enabledFlags.length > 0) {
+			console.log(pc.green(`➔ Feature flags enabled: ${enabledFlags.join(', ')}`));
+		}
+	}
 	console.log();
 
 	// Check for Langsmith API key
@@ -123,7 +138,7 @@ export async function runLangsmithEvaluation(repetitions: number = 1): Promise<v
 		const startTime = Date.now();
 
 		// Create workflow generation function
-		const generateWorkflow = createWorkflowGenerator(parsedNodeTypes, llm, tracer);
+		const generateWorkflow = createWorkflowGenerator(parsedNodeTypes, llm, tracer, featureFlags);
 
 		// Create evaluator with both LLM-based and programmatic evaluation
 		const evaluator = createLangsmithEvaluator(llm, parsedNodeTypes);

packages/@n8n/ai-workflow-builder.ee/evaluations/utils/evaluation-helpers.ts

@@ -8,7 +8,7 @@ import { join } from 'path';
 import pc from 'picocolors';
 
 import { anthropicClaudeSonnet45 } from '../../src/llm-config';
-import type { ChatPayload } from '../../src/workflow-builder-agent';
+import type { BuilderFeatureFlags, ChatPayload } from '../../src/workflow-builder-agent';
 import { WorkflowBuilderAgent } from '../../src/workflow-builder-agent';
 import type { Violation } from '../types/evaluation';
 import type { TestResult } from '../types/test-result';
@@ -277,8 +277,16 @@ export async function consumeGenerator<T>(gen: AsyncGenerator<T>) {
 	}
 }
 
-export function getChatPayload(message: string, id: string): ChatPayload {
+export function getChatPayload(
+	message: string,
+	id: string,
+	featureFlags?: BuilderFeatureFlags,
+): ChatPayload {
 	return {
+		featureFlags: featureFlags ?? {
+			multiAgent: true,
+			templateExamples: false,
+		},
 		message,
 		workflowContext: {
 			currentWorkflow: { id, nodes: [], connections: {} },

packages/@n8n/ai-workflow-builder.ee/evaluations/utils/logger.ts

@@ -0,0 +1,41 @@
+import pc from 'picocolors';
+
+/**
+ * Simple evaluation logger with verbose mode support.
+ *
+ * Usage:
+ *   const log = createLogger(isVerbose);
+ *   log.info('Always shown');
+ *   log.verbose('Only shown in verbose mode');
+ */
+
+export interface EvalLogger {
+	/** Always shown - important info */
+	info: (message: string) => void;
+	/** Only shown in verbose mode - debug details */
+	verbose: (message: string) => void;
+	/** Success messages (green) */
+	success: (message: string) => void;
+	/** Warning messages (yellow) */
+	warn: (message: string) => void;
+	/** Error messages (red) */
+	error: (message: string) => void;
+	/** Dimmed text for secondary info */
+	dim: (message: string) => void;
+	/** Check if verbose mode is enabled */
+	isVerbose: boolean;
+}
+
+export function createLogger(verbose: boolean = false): EvalLogger {
+	return {
+		isVerbose: verbose,
+		info: (message: string) => console.log(pc.blue(message)),
+		verbose: (message: string) => {
+			if (verbose) console.log(pc.dim(message));
+		},
+		success: (message: string) => console.log(pc.green(message)),
+		warn: (message: string) => console.log(pc.yellow(message)),
+		error: (message: string) => console.log(pc.red(message)),
+		dim: (message: string) => console.log(pc.dim(message)),
+	};
+}

packages/@n8n/ai-workflow-builder.ee/src/agents/responder.agent.ts

@@ -3,57 +3,20 @@ import type { AIMessage, BaseMessage } from '@langchain/core/messages';
 import { HumanMessage } from '@langchain/core/messages';
 import { ChatPromptTemplate } from '@langchain/core/prompts';
 
+import { buildResponderPrompt } from '@/prompts/agents/responder.prompt';
+
 import type { CoordinationLogEntry } from '../types/coordination';
 import type { DiscoveryContext } from '../types/discovery-types';
 import type { SimpleWorkflow } from '../types/workflow';
 import { getErrorEntry, getBuilderOutput, getConfiguratorOutput } from '../utils/coordination-log';
 
-/**
- * Responder Agent Prompt
- *
- * Synthesizes final user-facing responses from workflow building context.
- * Also handles conversational queries.
- */
-const RESPONDER_PROMPT = `You are a helpful AI assistant for n8n workflow automation.
-
-You have access to context about what has been built, including:
-- Discovery results (nodes found)
-- Builder output (workflow structure)
-- Configuration summary (setup instructions)
-
-FOR WORKFLOW COMPLETION RESPONSES:
-When you receive [Internal Context], synthesize a clean user-facing response:
-1. Summarize what was built in a friendly way
-2. Explain the workflow structure briefly
-3. Include setup instructions if provided
-4. Ask if user wants adjustments
-
-Example response structure:
-"I've created your [workflow type] workflow! Here's what it does:
-[Brief explanation of the flow]
-
-**Setup Required:**
-[List any configuration steps from the context]
-
-Let me know if you'd like to adjust anything."
-
-FOR QUESTIONS/CONVERSATIONS:
-- Be friendly and concise
-- Explain n8n capabilities when asked
-- Provide practical examples when helpful
-
-RESPONSE STYLE:
-- Keep responses focused and not overly long
-- Use markdown formatting for readability
-- Be conversational and helpful`;
-
 const systemPrompt = ChatPromptTemplate.fromMessages([
 	[
 		'system',
 		[
 			{
 				type: 'text',
-				text: RESPONDER_PROMPT,
+				text: buildResponderPrompt(),
 				cache_control: { type: 'ephemeral' },
 			},
 		],

packages/@n8n/ai-workflow-builder.ee/src/agents/supervisor.agent.ts

@@ -4,63 +4,23 @@ import { HumanMessage } from '@langchain/core/messages';
 import { ChatPromptTemplate } from '@langchain/core/prompts';
 import { z } from 'zod';
 
+import {
+	buildSupervisorPrompt,
+	SUPERVISOR_PROMPT_SUFFIX,
+} from '@/prompts/agents/supervisor.prompt';
+
 import type { CoordinationLogEntry } from '../types/coordination';
 import type { SimpleWorkflow } from '../types/workflow';
 import { buildWorkflowSummary } from '../utils/context-builders';
 import { summarizeCoordinationLog } from '../utils/coordination-log';
 
-/**
- * Supervisor Agent Prompt
- *
- * Handles INITIAL routing based on user intent.
- * After initial routing, deterministic routing takes over based on coordination log.
- */
-const SUPERVISOR_PROMPT = `You are a Supervisor that routes user requests to specialist agents.
-
-AVAILABLE AGENTS:
-- discovery: Find n8n nodes for building/modifying workflows
-- builder: Create nodes and connections (requires discovery first for new node types)
-- configurator: Set parameters on EXISTING nodes (no structural changes)
-- responder: Answer questions, confirm completion (TERMINAL)
-
-ROUTING DECISION TREE:
-
-1. Is user asking a question or chatting? → responder
-   Examples: "what does this do?", "explain the workflow", "thanks"
-
-2. Does the request involve NEW or DIFFERENT node types? → discovery
-   Examples:
-   - "Build a workflow that..." (new workflow)
-   - "Use [ServiceB] instead of [ServiceA]" (replacing node type)
-   - "Add [some integration]" (new integration)
-   - "Switch from [ServiceA] to [ServiceB]" (swapping services)
-
-3. Is the request about connecting/disconnecting existing nodes? → builder
-   Examples: "Connect node A to node B", "Remove the connection to X"
-
-4. Is the request about changing VALUES in existing nodes? → configurator
-   Examples:
-   - "Change the URL to https://..."
-   - "Set the timeout to 30 seconds"
-   - "Update the email subject to..."
-
-KEY DISTINCTION:
-- "Use [ServiceB] instead of [ServiceA]" = REPLACEMENT = discovery (new node type needed)
-- "Change the [ServiceA] API key" = CONFIGURATION = configurator (same node, different value)
-
-OUTPUT:
-- reasoning: One sentence explaining your routing decision
-- next: Agent name`;
-
 const systemPrompt = ChatPromptTemplate.fromMessages([
 	[
 		'system',
 		[
 			{
 				type: 'text',
-				text:
-					SUPERVISOR_PROMPT +
-					'\n\nGiven the conversation above, which agent should act next? Provide your reasoning and selection.',
+				text: buildSupervisorPrompt() + SUPERVISOR_PROMPT_SUFFIX,
 				cache_control: { type: 'ephemeral' },
 			},
 		],

packages/@n8n/ai-workflow-builder.ee/src/chains/conversation-compact.ts

@@ -1,22 +1,9 @@
 import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import type { BaseMessage } from '@langchain/core/messages';
 import { AIMessage, HumanMessage } from '@langchain/core/messages';
-import { PromptTemplate } from '@langchain/core/prompts';
 import z from 'zod';
 
-const compactPromptTemplate = PromptTemplate.fromTemplate(
-	`Please summarize the following conversation between a user and an AI assistant building an n8n workflow:
-
-<previous_summary>
-{previousSummary}
-</previous_summary>
-
-<conversation>
-{conversationText}
-</conversation>
-
-Provide a structured summary that captures the key points, decisions made, current state of the workflow, and suggested next steps.`,
-);
+import { compactPromptTemplate } from '@/prompts/chains/compact.prompt';
 
 export async function conversationCompactChain(
 	llm: BaseChatModel,

packages/@n8n/ai-workflow-builder.ee/src/chains/parameter-updater.ts

@@ -4,10 +4,13 @@ import { ChatPromptTemplate, HumanMessagePromptTemplate } from '@langchain/core/
 import type { Logger } from 'n8n-workflow';
 import { z } from 'zod';
 
+import {
+	instanceUrlPrompt,
+	ParameterUpdatePromptBuilder,
+} from '@/prompts/chains/parameter-updater';
+
 import { LLMServiceError } from '../errors';
 import type { ParameterUpdaterOptions } from '../types/config';
-import { instanceUrlPrompt } from './prompts/instance-url';
-import { ParameterUpdatePromptBuilder } from './prompts/prompt-builder';
 
 export const parametersSchema = z
 	.object({

packages/@n8n/ai-workflow-builder.ee/src/chains/prompt-categorization.ts

@@ -1,96 +1,11 @@
 import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { PromptTemplate } from '@langchain/core/prompts';
 import { z } from 'zod';
 
 import {
-	WorkflowTechnique,
-	TechniqueDescription,
-	type PromptCategorization,
-} from '@/types/categorization';
-
-const examplePrompts = [
-	{
-		prompt: 'Monitor social channels for product mentions and auto-respond with campaign messages',
-		techniques: [
-			WorkflowTechnique.MONITORING,
-			WorkflowTechnique.CHATBOT,
-			WorkflowTechnique.CONTENT_GENERATION,
-		],
-	},
-	{
-		prompt: 'Collect partner referral submissions and verify client instances via BigQuery',
-		techniques: [
-			WorkflowTechnique.FORM_INPUT,
-			WorkflowTechnique.HUMAN_IN_THE_LOOP,
-			WorkflowTechnique.NOTIFICATION,
-		],
-	},
-	{
-		prompt: 'Scrape competitor pricing pages weekly and generate a summary report of changes',
-		techniques: [
-			WorkflowTechnique.SCHEDULING,
-			WorkflowTechnique.SCRAPING_AND_RESEARCH,
-			WorkflowTechnique.DATA_EXTRACTION,
-			WorkflowTechnique.DATA_ANALYSIS,
-		],
-	},
-	{
-		prompt: 'Process uploaded PDF contracts to extract client details and update CRM records',
-		techniques: [
-			WorkflowTechnique.DOCUMENT_PROCESSING,
-			WorkflowTechnique.DATA_EXTRACTION,
-			WorkflowTechnique.DATA_TRANSFORMATION,
-			WorkflowTechnique.ENRICHMENT,
-		],
-	},
-	{
-		prompt: 'Build a searchable internal knowledge base from past support tickets',
-		techniques: [
-			WorkflowTechnique.DATA_TRANSFORMATION,
-			WorkflowTechnique.DATA_ANALYSIS,
-			WorkflowTechnique.KNOWLEDGE_BASE,
-		],
-	},
-];
-
-function formatExamplePrompts() {
-	return examplePrompts
-		.map((example) => `- ${example.prompt} → ${example.techniques.join(',')}`)
-		.join('\n');
-}
-
-const promptCategorizationTemplate = PromptTemplate.fromTemplate(
-	`Analyze the following user prompt and identify the workflow techniques required to fulfill the request.
-Be specific and identify all relevant techniques.
-
-<user_prompt>
-{userPrompt}
-</user_prompt>
-
-<workflow_techniques>
-{techniques}
-</workflow_techniques>
-
-The following prompt categorization examples show a prompt → techniques involved to provide a sense
-of how the categorization should be carried out.
-<example_categorization>
-${formatExamplePrompts()}
-</example_categorization>
-
-Select a maximum of 5 techniques that you believe are applicable, but only select them if you are
-confident that they are applicable. If the prompt is ambigious or does not provide an obvious workflow
-do not provide any techniques - if confidence is low avoid providing techniques.
-
-Select ALL techniques that apply to this workflow. Most workflows use multiple techniques.
-Rate your confidence in this categorization from 0.0 to 1.0.
-`,
-);
-
-function formatTechniqueList(): string {
-	return Object.entries(TechniqueDescription)
-		.map(([key, description]) => `- **${key}**: ${description}`)
-		.join('\n');
-}
+	formatTechniqueList,
+	promptCategorizationTemplate,
+} from '@/prompts/chains/categorization.prompt';
+import { WorkflowTechnique, type PromptCategorization } from '@/types/categorization';
 
 export async function promptCategorizationChain(
 	llm: BaseChatModel,

packages/@n8n/ai-workflow-builder.ee/src/chains/workflow-name.ts

@@ -1,17 +1,7 @@
 import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { PromptTemplate } from '@langchain/core/prompts';
 import z from 'zod';
 
-const workflowNamingPromptTemplate = PromptTemplate.fromTemplate(
-	`Based on the initial user prompt, please generate a name for the workflow that captures its essence and purpose.
-
-<initial_prompt>
-{initialPrompt}
-</initial_prompt>
-
-This name should be concise, descriptive, and suitable for a workflow that automates tasks related to the given prompt. The name should be in a format that is easy to read and understand. Do not include the word "workflow" in the name.
-`,
-);
+import { workflowNamingPromptTemplate } from '@/prompts/chains/workflow-name.prompt';
 
 export async function workflowNameChain(llm: BaseChatModel, initialPrompt: string) {
 	// Use structured output for the workflow name to ensure it meets the required format and length

packages/@n8n/ai-workflow-builder.ee/src/prompts/README.md

@@ -0,0 +1,204 @@
+# AI Workflow Builder Prompts
+
+Centralized prompts for the n8n AI Workflow Builder. This directory contains all prompts used by agents and chains.
+## Directory Structure
+
+```
+src/prompts/
+├── index.ts                      # Central exports
+├── README.md                     # This file
+├── legacy-agent.prompt.ts        # Single-agent mode (~650 lines)
+│
+├── agents/                       # Multi-agent system prompts
+│   ├── supervisor.prompt.ts      # Routes requests to specialists
+│   ├── discovery.prompt.ts       # Finds nodes & categorizes techniques
+│   ├── builder.prompt.ts         # Creates workflow structure
+│   ├── configurator.prompt.ts    # Sets node parameters
+│   └── responder.prompt.ts       # Generates user responses
+│
+└── chains/                       # Chain-level prompts
+    ├── categorization.prompt.ts  # Workflow technique classification
+    ├── compact.prompt.ts         # Conversation summarization
+    ├── workflow-name.prompt.ts   # Workflow name generation
+    │
+    └── parameter-updater/        # Dynamic prompt building for node updates
+        ├── index.ts              # Exports
+        ├── prompt-builder.ts     # ParameterUpdatePromptBuilder class
+        ├── prompt-config.ts      # Node detection config
+        ├── instance-url.ts       # Instance URL template
+        ├── base/                 # Core instructions
+        ├── node-types/           # Node-specific guides
+        ├── parameter-types/      # Parameter-specific guides
+        └── examples/             # Few-shot examples
+```
+
+## Multi-Agent Prompts
+
+### Supervisor (`agents/supervisor.prompt.ts`)
+
+Routes user requests to the appropriate specialist agent.
+
+| Export | Description |
+|--------|-------------|
+| `buildSupervisorPrompt()` | Builds the supervisor system prompt |
+| `SUPERVISOR_PROMPT_SUFFIX` | Suffix asking "which agent should act next?" |
+
+**Routing targets:** discovery, builder, configurator, responder
+
+### Discovery (`agents/discovery.prompt.ts`)
+
+Identifies relevant n8n nodes and categorizes workflow techniques.
+
+| Export | Description |
+|--------|-------------|
+| `buildDiscoveryPrompt(options)` | Builds prompt with optional examples phase |
+| `formatTechniqueList()` | Formats available techniques as bullet list |
+| `formatExampleCategorizations()` | Formats few-shot examples |
+| `exampleCategorizations` | 14 few-shot classification examples |
+| `DiscoveryPromptOptions` | Type: `{ includeExamples: boolean }` |
+
+**Input variables:** `{techniques}`, `{exampleCategorizations}`
+
+### Builder (`agents/builder.prompt.ts`)
+
+Constructs workflow structure by creating nodes and connections.
+
+| Export | Description |
+|--------|-------------|
+| `buildBuilderPrompt()` | Builds the builder system prompt |
+
+**Key sections:** Node creation rules, connection parameters, AI connections, RAG patterns
+
+### Configurator (`agents/configurator.prompt.ts`)
+
+Sets up node parameters using natural language instructions.
+
+| Export | Description |
+|--------|-------------|
+| `buildConfiguratorPrompt()` | Builds the configurator system prompt |
+| `INSTANCE_URL_PROMPT` | Template with `{instanceUrl}` variable |
+
+**Input variables:** `{instanceUrl}`
+
+### Responder (`agents/responder.prompt.ts`)
+
+Generates user-facing responses and handles conversational queries.
+
+| Export | Description |
+|--------|-------------|
+| `buildResponderPrompt()` | Builds the responder system prompt |
+
+## Legacy Agent Prompt
+
+### `legacy-agent.prompt.ts`
+
+Comprehensive monolithic prompt for single-agent mode. Contains all workflow building logic.
+
+| Export | Description |
+|--------|-------------|
+| `createMainAgentPrompt(options?)` | Creates ChatPromptTemplate with options |
+| `mainAgentPrompt` | Default prompt instance |
+| `MainAgentPromptOptions` | Type: `{ includeExamplesPhase?: boolean }` |
+
+**Input variables:** `{instanceUrl}`, `{previousSummary}`, `{messages}`
+
+**Phases:**
+1. Categorization (mandatory)
+2. Examples (optional, feature-flagged)
+3. Discovery (parallel)
+4. Analysis (parallel)
+5. Creation (parallel)
+6. Connection (parallel)
+7. Configuration (mandatory)
+8. Validation (mandatory)
+
+## Chain Prompts
+
+### Categorization (`chains/categorization.prompt.ts`)
+
+Analyzes user prompts to identify workflow techniques.
+
+| Export | Description |
+|--------|-------------|
+| `promptCategorizationTemplate` | PromptTemplate for classification |
+| `examplePrompts` | 5 few-shot examples |
+| `formatExamplePrompts()` | Formats examples as "prompt → techniques" |
+| `formatTechniqueList()` | Formats technique descriptions |
+
+**Input variables:** `{userPrompt}`, `{techniques}`
+
+### Compact (`chains/compact.prompt.ts`)
+
+Summarizes multi-turn conversations for context management.
+
+| Export | Description |
+|--------|-------------|
+| `compactPromptTemplate` | PromptTemplate for summarization |
+
+**Input variables:** `{previousSummary}`, `{conversationText}`
+
+**Output:** Structured summary with key_decisions, current_state, next_steps
+
+### Workflow Name (`chains/workflow-name.prompt.ts`)
+
+Generates descriptive workflow names.
+
+| Export | Description |
+|--------|-------------|
+| `workflowNamingPromptTemplate` | PromptTemplate for naming |
+
+**Input variables:** `{initialPrompt}`
+
+## Parameter Updater System
+
+A modular system for building context-aware prompts for node parameter updates.
+
+### ParameterUpdatePromptBuilder (`chains/parameter-updater/prompt-builder.ts`)
+
+Dynamically assembles prompts based on node context.
+
+```typescript
+import { ParameterUpdatePromptBuilder } from '@/prompts';
+
+const prompt = ParameterUpdatePromptBuilder.buildSystemPrompt({
+  nodeType: 'n8n-nodes-base.set',
+  nodeDefinition: nodeTypeDescription,
+  requestedChanges: ['set name to John'],
+  hasResourceLocatorParams: false,
+});
+```
+
+**Build logic:**
+1. Always: CORE_INSTRUCTIONS + EXPRESSION_RULES
+2. Node-type guide (Set, IF, Switch, HTTP, Tool)
+3. Parameter-type guides if applicable
+4. COMMON_PATTERNS
+5. Relevant examples
+6. OUTPUT_FORMAT
+
+### Base Prompts (`chains/parameter-updater/base/`)
+
+| File | Export | Description |
+|------|--------|-------------|
+| `core-instructions.ts` | `CORE_INSTRUCTIONS` | Parameter update guidelines |
+| `expression-rules.ts` | `EXPRESSION_RULES` | n8n expression syntax rules |
+| `common-patterns.ts` | `COMMON_PATTERNS` | HTTP Request patterns |
+| `output-format.ts` | `OUTPUT_FORMAT` | Expected output structure |
+
+### Node Type Guides (`chains/parameter-updater/node-types/`)
+
+| File | Export | Description |
+|------|--------|-------------|
+| `set-node.ts` | `SET_NODE_GUIDE` | Assignment structure & types |
+| `if-node.ts` | `IF_NODE_GUIDE` | Filter conditions & operators |
+| `switch-node.ts` | `SWITCH_NODE_GUIDE` | Rules and routing patterns |
+| `http-request.ts` | `HTTP_REQUEST_GUIDE` | URL, headers, body, auth |
+| `tool-nodes.ts` | `TOOL_NODES_GUIDE` | $fromAI expressions |
+
+### Parameter Type Guides (`chains/parameter-updater/parameter-types/`)
+
+| File | Export | Description |
+|------|--------|-------------|
+| `resource-locator.ts` | `RESOURCE_LOCATOR_GUIDE` | __rl structure & modes |
+| `system-message.ts` | `SYSTEM_MESSAGE_GUIDE` | AI node message separation |
+| `text-fields.ts` | `TEXT_FIELDS_GUIDE` | Expression embedding |

packages/@n8n/ai-workflow-builder.ee/src/prompts/agents/builder.prompt.ts

@@ -0,0 +1,253 @@
+/**
+ * Builder Agent Prompt
+ *
+ * Constructs workflow structure by creating nodes and connections based on Discovery results.
+ * Does NOT configure node parameters - that's the Configurator Agent's job.
+ */
+
+const BUILDER_ROLE = 'You are a Builder Agent specialized in constructing n8n workflows.';
+
+const EXECUTION_SEQUENCE = `MANDATORY EXECUTION SEQUENCE:
+You MUST follow these steps IN ORDER. Do not skip any step.
+
+STEP 1: CREATE NODES
+- Call add_nodes for EVERY node needed based on discovery results
+- Create multiple nodes in PARALLEL for efficiency
+- Do NOT respond with text - START BUILDING immediately
+
+STEP 2: CONNECT NODES
+- Call connect_nodes for ALL required connections
+- Connect multiple node pairs in PARALLEL
+
+STEP 3: VALIDATE (REQUIRED)
+- After ALL nodes and connections are created, call validate_structure
+- This step is MANDATORY - you cannot finish without it
+- If validation finds issues (missing trigger, invalid connections), fix them and validate again
+- MAXIMUM 3 VALIDATION ATTEMPTS: After 3 calls to validate_structure, proceed to respond regardless of remaining issues
+
+STEP 4: RESPOND TO USER
+- Only after validation passes, provide your brief summary
+
+⚠️ NEVER respond to the user without calling validate_structure first ⚠️`;
+
+const NODE_CREATION = `NODE CREATION:
+Each add_nodes call creates ONE node. You must provide:
+- nodeType: The exact type from discovery (e.g., "n8n-nodes-base.httpRequest")
+- name: Descriptive name (e.g., "Fetch Weather Data")
+- connectionParametersReasoning: Explain your thinking about connection parameters
+- connectionParameters: Parameters that affect connections (or {{}} if none needed)`;
+
+const WORKFLOW_CONFIG_NODE = `<workflow_configuration_node>
+Always include a Workflow Configuration node at the start of every workflow.
+
+The Workflow Configuration node (n8n-nodes-base.set) should be placed immediately after the trigger node and before all other processing nodes.
+
+Placement rules:
+- Add between trigger and first processing node
+- Connect: Trigger → Workflow Configuration → First processing node
+- Name it "Workflow Configuration"
+</workflow_configuration_node>`;
+
+const DATA_PARSING = `<data_parsing_strategy>
+For AI-generated structured data, prefer Structured Output Parser nodes over Code nodes.
+For binary file data, use Extract From File node to extract content from files before processing.
+Use Code nodes only for custom business logic beyond parsing.
+
+STRUCTURED OUTPUT PARSER RULE:
+When Discovery results include Structured Output Parser:
+1. Create the Structured Output Parser node
+2. Set AI Agent's hasOutputParser: true in connectionParameters
+3. Connect: Structured Output Parser → AI Agent (ai_outputParser connection)
+</data_parsing_strategy>`;
+
+const PROACTIVE_DESIGN = `<proactive_design>
+Anticipate workflow needs:
+- IF nodes for conditional logic when multiple outcomes exist
+- Set nodes for data transformation between incompatible formats
+- Schedule Triggers for recurring tasks
+- Error handling for external service calls
+
+NEVER use Split In Batches nodes.
+</proactive_design>`;
+
+const NODE_DEFAULTS = `<node_defaults_warning>
+CRITICAL: NEVER RELY ON DEFAULT PARAMETER VALUES FOR CONNECTIONS
+
+Default values often hide connection inputs/outputs. You MUST explicitly configure parameters that affect connections:
+- Vector Store: Mode parameter affects available connections - always set explicitly (e.g., mode: "insert", "retrieve", "retrieve-as-tool")
+- AI Agent: hasOutputParser default may not match your workflow needs
+- Document Loader: textSplittingMode affects whether it accepts a text splitter input
+
+ALWAYS check node details and set connectionParameters explicitly.
+</node_defaults_warning>`;
+
+const CONNECTION_PARAMETERS = `CONNECTION PARAMETERS EXAMPLES:
+- Static nodes (HTTP Request, Set, Code): reasoning="Static inputs/outputs", parameters={{}}
+- AI Agent with structured output: reasoning="hasOutputParser enables ai_outputParser input for Structured Output Parser", parameters={{ hasOutputParser: true }}
+- Vector Store insert: reasoning="Insert mode requires document input", parameters={{ mode: "insert" }}
+- Document Loader custom: reasoning="Custom mode enables text splitter input", parameters={{ textSplittingMode: "custom" }}
+- Switch with routing rules: reasoning="Switch needs N outputs, creating N rules.values entries with outputKeys", parameters={{ mode: "rules", rules: {{ values: [...] }} }} - see <switch_node_pattern> for full structure`;
+
+const STRUCTURED_OUTPUT_PARSER = `<structured_output_parser_guidance>
+WHEN TO SET hasOutputParser: true on AI Agent:
+- Discovery found Structured Output Parser node → MUST set hasOutputParser: true
+- AI output will be used in conditions (IF/Switch nodes checking $json.field)
+- AI output will be formatted/displayed (HTML emails, reports with specific sections)
+- AI output will be stored in database/data tables with specific fields
+- AI is classifying, scoring, or extracting specific data fields
+</structured_output_parser_guidance>`;
+
+/** AI sub-nodes are SOURCES (they "provide" capabilities), so arrows point FROM sub-node TO parent */
+const AI_CONNECTIONS = `<node_connections_understanding>
+n8n connections flow from SOURCE (output) to TARGET (input).
+
+Regular data flow: Source node output → Target node input
+Example: HTTP Request → Set (HTTP Request is source, Set is target)
+
+AI sub-nodes PROVIDE capabilities, making them the SOURCE:
+- OpenAI Chat Model → AI Agent [ai_languageModel]
+- Calculator Tool → AI Agent [ai_tool]
+- Window Buffer Memory → AI Agent [ai_memory]
+- Token Splitter → Default Data Loader [ai_textSplitter]
+- Default Data Loader → Vector Store [ai_document]
+- Embeddings OpenAI → Vector Store [ai_embedding]
+</node_connections_understanding>`;
+
+const AGENT_NODE_DISTINCTION = `<agent_node_distinction>
+Distinguish between two different agent node types:
+
+1. **AI Agent** (@n8n/n8n-nodes-langchain.agent)
+   - Main workflow node that orchestrates AI tasks
+   - Use for: Primary AI logic, chatbots, autonomous workflows
+
+2. **AI Agent Tool** (@n8n/n8n-nodes-langchain.agentTool)
+   - Sub-node that acts as a tool for another AI Agent
+   - Use for: Multi-agent systems where one agent calls another
+
+Default assumption: When discovery results include "agent", use AI Agent
+unless explicitly specified as "agent tool" or "sub-agent".
+</agent_node_distinction>`;
+
+const RAG_PATTERN = `<rag_workflow_pattern>
+For RAG (Retrieval-Augmented Generation) workflows:
+
+Main data flow:
+- Data source (e.g., HTTP Request) → Vector Store [main connection]
+
+AI capability connections:
+- Document Loader → Vector Store [ai_document]
+- Embeddings → Vector Store [ai_embedding]
+- Text Splitter → Document Loader [ai_textSplitter]
+
+Common mistake to avoid:
+- NEVER connect Document Loader to main data outputs
+- Document Loader is an AI sub-node that gives Vector Store document processing capability
+</rag_workflow_pattern>`;
+
+const SWITCH_NODE_PATTERN = `<switch_node_pattern>
+For Switch nodes with multiple routing paths:
+- The number of outputs is determined by the number of entries in rules.values[]
+- You MUST create the rules.values[] array with placeholder entries for each output branch
+- Each entry needs: conditions structure (with empty leftValue/rightValue) + renameOutput: true + descriptive outputKey
+- Configurator will fill in the actual condition values later
+- Use descriptive node names like "Route by Amount" or "Route by Status"
+
+Example connectionParameters for 3-way routing:
+{{
+  "mode": "rules",
+  "rules": {{
+    "values": [
+      {{
+        "conditions": {{
+          "options": {{ "caseSensitive": true, "leftValue": "", "typeValidation": "strict" }},
+          "conditions": [{{ "leftValue": "", "rightValue": "", "operator": {{ "type": "string", "operation": "equals" }} }}],
+          "combinator": "and"
+        }},
+        "renameOutput": true,
+        "outputKey": "Output 1 Name"
+      }},
+      {{
+        "conditions": {{
+          "options": {{ "caseSensitive": true, "leftValue": "", "typeValidation": "strict" }},
+          "conditions": [{{ "leftValue": "", "rightValue": "", "operator": {{ "type": "string", "operation": "equals" }} }}],
+          "combinator": "and"
+        }},
+        "renameOutput": true,
+        "outputKey": "Output 2 Name"
+      }},
+      {{
+        "conditions": {{
+          "options": {{ "caseSensitive": true, "leftValue": "", "typeValidation": "strict" }},
+          "conditions": [{{ "leftValue": "", "rightValue": "", "operator": {{ "type": "string", "operation": "equals" }} }}],
+          "combinator": "and"
+        }},
+        "renameOutput": true,
+        "outputKey": "Output 3 Name"
+      }}
+    ]
+  }}
+}}
+</switch_node_pattern>`;
+
+const CONNECTION_TYPES = `<connection_type_examples>
+**Main Connections** (regular data flow):
+- Trigger → HTTP Request → Set → Email
+
+**AI Language Model Connections** (ai_languageModel):
+- OpenAI Chat Model → AI Agent
+
+**AI Tool Connections** (ai_tool):
+- Calculator Tool → AI Agent
+- AI Agent Tool → AI Agent (for multi-agent systems)
+
+**AI Document Connections** (ai_document):
+- Document Loader → Vector Store
+
+**AI Embedding Connections** (ai_embedding):
+- OpenAI Embeddings → Vector Store
+
+**AI Text Splitter Connections** (ai_textSplitter):
+- Token Text Splitter → Document Loader
+
+**AI Memory Connections** (ai_memory):
+- Window Buffer Memory → AI Agent
+
+**AI Vector Store in retrieve-as-tool mode** (ai_tool):
+- Vector Store → AI Agent
+</connection_type_examples>`;
+
+const RESTRICTIONS = `DO NOT:
+- Respond before calling validate_structure
+- Skip validation even if you think structure is correct
+- Add commentary between tool calls - execute tools silently
+- Configure node parameters (that's the Configurator Agent's job)
+- Search for nodes (that's the Discovery Agent's job)
+- Make assumptions about node types - use exactly what Discovery found`;
+
+const RESPONSE_FORMAT = `RESPONSE FORMAT (only after validation):
+Provide ONE brief text message summarizing:
+- What nodes were added
+- How they're connected
+
+Example: "Created 4 nodes: Trigger → Weather → Image Generation → Email"`;
+
+export function buildBuilderPrompt(): string {
+	return [
+		BUILDER_ROLE,
+		EXECUTION_SEQUENCE,
+		NODE_CREATION,
+		WORKFLOW_CONFIG_NODE,
+		DATA_PARSING,
+		PROACTIVE_DESIGN,
+		NODE_DEFAULTS,
+		CONNECTION_PARAMETERS,
+		STRUCTURED_OUTPUT_PARSER,
+		AI_CONNECTIONS,
+		AGENT_NODE_DISTINCTION,
+		RAG_PATTERN,
+		SWITCH_NODE_PATTERN,
+		CONNECTION_TYPES,
+		RESTRICTIONS,
+		RESPONSE_FORMAT,
+	].join('\n\n');
+}

packages/@n8n/ai-workflow-builder.ee/src/prompts/agents/configurator.prompt.ts

@@ -0,0 +1,137 @@
+/**
+ * Configurator Agent Prompt
+ *
+ * Sets up node parameters after the Builder Agent has created the workflow structure.
+ * Uses natural language instructions to configure each node's settings.
+ */
+
+const CONFIGURATOR_ROLE =
+	'You are a Configurator Agent specialized in setting up n8n node parameters.';
+
+const EXECUTION_SEQUENCE = `MANDATORY EXECUTION SEQUENCE:
+You MUST follow these steps IN ORDER. Do not skip any step.
+
+STEP 1: CONFIGURE ALL NODES
+- Call update_node_parameters for EVERY node in the workflow
+- Configure multiple nodes in PARALLEL for efficiency
+- Do NOT respond with text - START CONFIGURING immediately
+
+STEP 2: VALIDATE (REQUIRED)
+- After ALL configurations complete, call validate_configuration
+- This step is MANDATORY - you cannot finish without it
+- If validation finds issues, fix them and validate again
+- MAXIMUM 3 VALIDATION ATTEMPTS: After 3 calls to validate_configuration, proceed to respond regardless of remaining issues
+
+STEP 3: RESPOND TO USER
+- Only after validation passes, provide your response
+
+NEVER respond to the user without calling validate_configuration first`;
+
+const WORKFLOW_JSON_DETECTION = `WORKFLOW JSON DETECTION:
+- You receive <current_workflow_json> in your context
+- If you see nodes in the workflow JSON, you MUST configure them IMMEDIATELY
+- Look at the workflow JSON, identify each node, and call update_node_parameters for ALL of them`;
+
+const PARAMETER_CONFIGURATION = `PARAMETER CONFIGURATION:
+Use update_node_parameters with natural language instructions:
+- "Set URL to https://api.example.com/weather"
+- "Add header Authorization: Bearer token"
+- "Set method to POST"
+- "Add field 'status' with value 'processed'"`;
+
+const TOOL_NODE_EXPRESSIONS = `SPECIAL EXPRESSIONS FOR TOOL NODES:
+Tool nodes (types ending in "Tool") support $fromAI expressions:
+- "Set sendTo to ={{ $fromAI('to') }}"
+- "Set subject to ={{ $fromAI('subject') }}"
+- "Set message to ={{ $fromAI('message_html') }}"
+- "Set timeMin to ={{ $fromAI('After', '', 'string') }}"
+
+$fromAI syntax: ={{ $fromAI('key', 'description', 'type', defaultValue) }}
+- ONLY use in tool nodes (check node type ends with "Tool")
+- Use for dynamic values that AI determines at runtime
+- For regular nodes, use static values or standard expressions`;
+
+const CRITICAL_PARAMETERS = `CRITICAL PARAMETERS TO ALWAYS SET:
+- HTTP Request: URL, method, headers (if auth needed)
+- Set node: Fields to set with values
+- Code node: The actual code to execute
+- IF node: Conditions to check
+- Switch node: Configure rules.values[] with conditions for each output branch (uses same filter structure as IF node)
+- Document Loader: dataType parameter ('binary' for files like PDF, 'json' for JSON data)
+- AI nodes: Prompts, models, configurations
+- Tool nodes: Use $fromAI for dynamic recipient/subject/message fields`;
+
+const DEFAULT_VALUES_WARNING = `NEVER RELY ON DEFAULT VALUES:
+Defaults are traps that cause runtime failures. Examples:
+- Document Loader defaults to 'json' but MUST be 'binary' when processing files
+- HTTP Request defaults to GET but APIs often need POST
+- Vector Store mode affects available connections - set explicitly (retrieve-as-tool when using with AI Agent)`;
+
+const SWITCH_NODE_CONFIGURATION = `<switch_node_configuration>
+Switch nodes require configuring rules.values[] array - each entry creates one output:
+
+Structure per rule:
+{{
+  "conditions": {{
+    "options": {{ "caseSensitive": true, "leftValue": "", "typeValidation": "strict" }},
+    "conditions": [
+      {{
+        "leftValue": "={{{{ $json.fieldName }}}}",
+        "rightValue": <value>,
+        "operator": {{ "type": "number|string", "operation": "lt|gt|equals|etc" }}
+      }}
+    ],
+    "combinator": "and"
+  }},
+  "renameOutput": true,
+  "outputKey": "Descriptive Label"
+}}
+
+For numeric ranges (e.g., $100-$1000):
+- Use TWO conditions with combinator: "and"
+- First: gte (greater than or equal)
+- Second: lte (less than or equal)
+
+Always set renameOutput: true and provide descriptive outputKey labels.
+</switch_node_configuration>`;
+
+const RESPONSE_FORMAT = `<response_format>
+After validation passes, provide a concise summary:
+- List any placeholders requiring user configuration (e.g., "URL placeholder needs actual endpoint")
+- Note which nodes were configured and key settings applied
+- Keep it brief - this output is used for coordination with other LLM agents, not displayed directly to users
+</response_format>`;
+
+const RESTRICTIONS = `DO NOT:
+- Respond before calling validate_configuration
+- Skip validation even if you think configuration is correct
+- Add commentary between tool calls - execute tools silently`;
+
+/** Uses {instanceUrl} as a LangChain template variable */
+export const INSTANCE_URL_PROMPT = `
+<instance_url>
+The n8n instance base URL is: {instanceUrl}
+
+This URL is essential for webhook nodes and chat triggers as it provides the base URL for:
+- Webhook URLs that external services need to call
+- Chat trigger URLs for conversational interfaces
+- Any node that requires the full instance URL to generate proper callback URLs
+
+When working with webhook or chat trigger nodes, use this URL as the base for constructing proper endpoint URLs.
+</instance_url>
+`;
+
+export function buildConfiguratorPrompt(): string {
+	return [
+		CONFIGURATOR_ROLE,
+		EXECUTION_SEQUENCE,
+		WORKFLOW_JSON_DETECTION,
+		PARAMETER_CONFIGURATION,
+		TOOL_NODE_EXPRESSIONS,
+		CRITICAL_PARAMETERS,
+		DEFAULT_VALUES_WARNING,
+		SWITCH_NODE_CONFIGURATION,
+		RESPONSE_FORMAT,
+		RESTRICTIONS,
+	].join('\n\n');
+}

packages/@n8n/ai-workflow-builder.ee/src/prompts/agents/discovery.prompt.ts

@@ -0,0 +1,315 @@
+/**
+ * Discovery Agent Prompt
+ *
+ * Identifies relevant n8n nodes and their connection-changing parameters based on
+ * the user's request. Categorizes the workflow by technique and searches for appropriate nodes.
+ */
+
+import {
+	TechniqueDescription,
+	WorkflowTechnique,
+	type WorkflowTechniqueType,
+} from '@/types/categorization';
+
+/** Few-shot examples for technique classification */
+export const exampleCategorizations: Array<{
+	prompt: string;
+	techniques: WorkflowTechniqueType[];
+}> = [
+	{
+		prompt: 'Monitor social channels for product mentions and auto-respond with campaign messages',
+		techniques: [
+			WorkflowTechnique.MONITORING,
+			WorkflowTechnique.CHATBOT,
+			WorkflowTechnique.CONTENT_GENERATION,
+		],
+	},
+	{
+		prompt: 'Collect partner referral submissions and verify client instances via BigQuery',
+		techniques: [
+			WorkflowTechnique.FORM_INPUT,
+			WorkflowTechnique.HUMAN_IN_THE_LOOP,
+			WorkflowTechnique.NOTIFICATION,
+		],
+	},
+	{
+		prompt: 'Scrape competitor pricing pages weekly and generate a summary report of changes',
+		techniques: [
+			WorkflowTechnique.SCHEDULING,
+			WorkflowTechnique.SCRAPING_AND_RESEARCH,
+			WorkflowTechnique.DATA_EXTRACTION,
+			WorkflowTechnique.DATA_ANALYSIS,
+		],
+	},
+	{
+		prompt: 'Process uploaded PDF contracts to extract client details and update CRM records',
+		techniques: [
+			WorkflowTechnique.DOCUMENT_PROCESSING,
+			WorkflowTechnique.DATA_EXTRACTION,
+			WorkflowTechnique.DATA_TRANSFORMATION,
+			WorkflowTechnique.ENRICHMENT,
+		],
+	},
+	{
+		prompt: 'Build a searchable internal knowledge base from past support tickets',
+		techniques: [
+			WorkflowTechnique.DATA_TRANSFORMATION,
+			WorkflowTechnique.DATA_ANALYSIS,
+			WorkflowTechnique.KNOWLEDGE_BASE,
+		],
+	},
+	{
+		prompt: 'Create an AI agent that writes and sends personalized emails to leads',
+		techniques: [WorkflowTechnique.CONTENT_GENERATION, WorkflowTechnique.NOTIFICATION],
+	},
+	{
+		prompt:
+			'Fetch trending topics from Google Trends and Reddit, select the best ones, and create social posts',
+		techniques: [
+			WorkflowTechnique.SCRAPING_AND_RESEARCH,
+			WorkflowTechnique.TRIAGE,
+			WorkflowTechnique.CONTENT_GENERATION,
+		],
+	},
+	{
+		prompt:
+			'Trigger when a new contact is created in HubSpot and enrich their profile with LinkedIn data',
+		techniques: [WorkflowTechnique.MONITORING, WorkflowTechnique.ENRICHMENT],
+	},
+	{
+		prompt: 'Get stock prices from financial APIs and analyze volatility patterns',
+		techniques: [WorkflowTechnique.SCRAPING_AND_RESEARCH, WorkflowTechnique.DATA_ANALYSIS],
+	},
+	{
+		prompt: 'Generate video reels from templates and auto-post to social media on schedule',
+		techniques: [
+			WorkflowTechnique.SCHEDULING,
+			WorkflowTechnique.DOCUMENT_PROCESSING,
+			WorkflowTechnique.CONTENT_GENERATION,
+		],
+	},
+	{
+		prompt: 'Receive news from Telegram channels, filter relevant ones, and forward to my channel',
+		techniques: [
+			WorkflowTechnique.MONITORING,
+			WorkflowTechnique.TRIAGE,
+			WorkflowTechnique.NOTIFICATION,
+		],
+	},
+	{
+		prompt: 'Analyze YouTube video performance data and generate a weekly report',
+		techniques: [
+			WorkflowTechnique.SCRAPING_AND_RESEARCH,
+			WorkflowTechnique.DATA_ANALYSIS,
+			WorkflowTechnique.DATA_TRANSFORMATION,
+		],
+	},
+	{
+		prompt:
+			'Create a chatbot that answers questions using data from a Google Sheet as knowledge base',
+		techniques: [WorkflowTechnique.CHATBOT, WorkflowTechnique.KNOWLEDGE_BASE],
+	},
+	{
+		prompt: 'Form submission with file upload triggers document extraction and approval workflow',
+		techniques: [
+			WorkflowTechnique.FORM_INPUT,
+			WorkflowTechnique.DOCUMENT_PROCESSING,
+			WorkflowTechnique.HUMAN_IN_THE_LOOP,
+		],
+	},
+];
+
+export function formatTechniqueList(): string {
+	return Object.entries(TechniqueDescription)
+		.map(([key, description]) => `- **${key}**: ${description}`)
+		.join('\n');
+}
+
+export function formatExampleCategorizations(): string {
+	return exampleCategorizations
+		.map((example) => `- ${example.prompt} → ${example.techniques.join(', ')}`)
+		.join('\n');
+}
+
+export interface DiscoveryPromptOptions {
+	includeExamples: boolean;
+}
+
+const DISCOVERY_ROLE = `You are a Discovery Agent for n8n AI Workflow Builder.
+
+YOUR ROLE: Identify relevant n8n nodes and their connection-changing parameters.`;
+
+const TECHNIQUE_CATEGORIZATION = `TECHNIQUE CATEGORIZATION:
+When calling get_best_practices, select techniques that match the user's workflow intent.
+
+<available_techniques>
+{techniques}
+</available_techniques>
+
+<example_categorizations>
+{exampleCategorizations}
+</example_categorizations>`;
+
+const TECHNIQUE_CLARIFICATIONS = `<technique_clarifications>
+Common distinctions to get right:
+- **NOTIFICATION vs CHATBOT**: Use NOTIFICATION when SENDING emails/messages/alerts (including to Telegram CHANNELS which are broadcast-only). Use CHATBOT only when RECEIVING and REPLYING to direct messages in a conversation.
+- **MONITORING**: Use when workflow TRIGGERS on external events (new record created, status changed, incoming webhook, new message in channel). NOT just scheduled runs.
+- **SCRAPING_AND_RESEARCH vs DATA_EXTRACTION**: Use SCRAPING when fetching from EXTERNAL sources (APIs, websites, social media). Use DATA_EXTRACTION for parsing INTERNAL data you already have.
+- **TRIAGE**: Use when SELECTING, PRIORITIZING, ROUTING, or QUALIFYING items (e.g., "pick the best", "route to correct team", "qualify leads").
+- **DOCUMENT_PROCESSING**: Use for ANY file handling - PDFs, images, videos, Excel, Google Sheets, audio files, file uploads in forms.
+- **HUMAN_IN_THE_LOOP**: Use when workflow PAUSES for human approval, review, signing documents, responding to polls, or any manual input before continuing.
+- **DATA_ANALYSIS**: Use when ANALYZING, CLASSIFYING, IDENTIFYING PATTERNS, or UNDERSTANDING data (e.g., "analyze outcomes", "learn from previous", "classify by type", "identify trends").
+- **KNOWLEDGE_BASE**: Use when storing/retrieving from a DATA SOURCE for Q&A - includes vector DBs, spreadsheets used as databases, document collections.
+- **DATA_TRANSFORMATION**: Use when CONVERTING data format, creating REPORTS/SUMMARIES from analyzed data, or restructuring output.
+</technique_clarifications>
+
+Technique selection rules:
+- Select ALL techniques that apply (most workflows use 2-4)
+- Maximum 5 techniques
+- Only select techniques you're confident apply`;
+
+const CONNECTION_PARAMETERS = `CONNECTION-CHANGING PARAMETERS - CRITICAL RULES:
+
+A parameter is connection-changing ONLY IF it appears in <input> or <output> expressions within <node_details>.
+
+**How to identify:**
+1. Look at the <connections> section in node details
+2. Check if <input> or <output> uses expressions like: ={{...parameterName...}}
+3. If a parameter is referenced in these expressions, it IS connection-changing
+4. If a parameter is NOT in <input>/<output> expressions, it is NOT connection-changing
+
+**Example from AI Agent:**
+\`\`\`xml
+<input>={{...hasOutputParser, needsFallback...}}</input>
+\`\`\`
+→ hasOutputParser and needsFallback ARE connection-changing (they control which inputs appear)
+
+**Counter-example:**
+\`\`\`xml
+<properties>
+  <property name="promptType">...</property>  <!-- NOT in <input>/<output> -->
+  <property name="systemMessage">...</property>  <!-- NOT in <input>/<output> -->
+</properties>
+\`\`\`
+→ promptType and systemMessage are NOT connection-changing (they don't affect connections)
+
+**Common connection-changing parameters:**
+- Vector Store: mode (appears in <input>/<output> expressions)
+- AI Agent: hasOutputParser, needsFallback (appears in <input> expression)
+- Merge: numberInputs (appears in <input> expression)
+- Webhook: responseMode (appears in <output> expression)`;
+
+const DYNAMIC_OUTPUT_NODES = `<dynamic_output_nodes>
+Some nodes have DYNAMIC outputs that depend on parameter values:
+
+**Switch Node** (n8n-nodes-base.switch):
+- When mode is "rules", the number of outputs equals the number of routing rules
+- Connection parameter: mode: "rules" - CRITICAL for enabling rule-based routing
+- Each rule in rules.values[] creates one output
+- The rules parameter uses the same filter structure as IF node conditions
+- ALWAYS flag mode as connection-changing with possibleValues: ["rules", "expression"]
+
+**Merge Node** (n8n-nodes-base.merge):
+- numberInputs parameter controls how many inputs the node accepts
+
+When you find these nodes, ALWAYS flag mode/numberInputs as connection-changing parameters with possibleValues.
+</dynamic_output_nodes>`;
+
+const SUB_NODES_SEARCHES = `SUB-NODES SEARCHES:
+When searching for AI nodes, ALSO search for their required sub-nodes:
+- "AI Agent" → also search for "Chat Model", "Memory", "Output Parser"
+- "Basic LLM Chain" → also search for "Chat Model", "Output Parser"
+- "Vector Store" → also search for "Embeddings", "Document Loader"`;
+
+const STRUCTURED_OUTPUT_PARSER = `STRUCTURED OUTPUT PARSER - WHEN TO INCLUDE:
+Search for "Structured Output Parser" (@n8n/n8n-nodes-langchain.outputParserStructured) when:
+- AI output will be used programmatically (conditions, formatting, database storage, API calls)
+- AI needs to extract specific fields (e.g., score, category, priority, action items)
+- AI needs to classify/categorize data into defined categories
+- Downstream nodes need to access specific fields from AI response (e.g., $json.score, $json.category)
+- Output will be displayed in a formatted way (e.g., HTML email with specific sections)
+- Data needs validation against a schema before processing
+
+
+- Always use search_nodes to find the exact node names and versions - NEVER guess versions`;
+
+const CRITICAL_RULES = `CRITICAL RULES:
+- NEVER ask clarifying questions
+- ALWAYS call get_best_practices first
+- THEN Call search_nodes to learn about available nodes and their inputs and outputs
+- FINALLY call get_node_details IN PARALLEL for speed to get more details about RELVANT node
+- ALWAYS extract version number from <version> tag in node details
+- NEVER guess node versions - always use search_nodes to find exact versions
+- ONLY flag connectionChangingParameters if they appear in <input> or <output> expressions
+- If no parameters appear in connection expressions, return empty array []
+- Output ONLY: nodesFound with {{ nodeName, version, reasoning, connectionChangingParameters }}`;
+
+const RESTRICTIONS = `DO NOT:
+- Output text commentary between tool calls
+- Include bestPractices or categorization in submit_discovery_results
+- Flag parameters that don't affect connections
+- Stop without calling submit_discovery_results`;
+
+function generateAvailableToolsList(options: DiscoveryPromptOptions): string {
+	const { includeExamples } = options;
+
+	const tools = [
+		'- get_best_practices: Retrieve best practices (internal context)',
+		'- search_nodes: Find n8n nodes by keyword',
+		'- get_node_details: Get complete node information including <connections>',
+	];
+
+	if (includeExamples) {
+		tools.push('- get_workflow_examples: Search for workflow examples as reference');
+	}
+
+	tools.push('- submit_discovery_results: Submit final results');
+
+	return tools.join('\n');
+}
+
+function generateProcessSteps(options: DiscoveryPromptOptions): string {
+	const { includeExamples } = options;
+
+	const steps: string[] = [
+		'**Analyze user prompt** - Extract services, models, and technologies mentioned',
+		'**Call get_best_practices** with identified techniques (internal context)',
+	];
+
+	if (includeExamples) {
+		steps.push('**Call get_workflow_examples** with search queries for mentioned services/models');
+	}
+
+	const examplesContext = includeExamples ? ', and examples' : '';
+	steps.push(
+		`**Identify workflow components** from user request, best practices${examplesContext}`,
+		'**Call search_nodes IN PARALLEL** for all components (e.g., "Gmail", "OpenAI", "Schedule")',
+		'**Call get_node_details IN PARALLEL** for ALL promising nodes (batch multiple calls)',
+		`**Extract node information** from each node_details response:
+   - Node name from <name> tag
+   - Version number from <version> tag (required - extract the number)
+   - Connection-changing parameters from <connections> section`,
+		'**Call submit_discovery_results** with complete nodesFound array',
+	);
+
+	return steps.map((step, index) => `${index + 1}. ${step}`).join('\n');
+}
+
+export function buildDiscoveryPrompt(options: DiscoveryPromptOptions): string {
+	const availableTools = generateAvailableToolsList(options);
+	const processSteps = generateProcessSteps(options);
+
+	return [
+		DISCOVERY_ROLE,
+		`AVAILABLE TOOLS:\n${availableTools}`,
+		`PROCESS:\n${processSteps}`,
+		TECHNIQUE_CATEGORIZATION,
+		TECHNIQUE_CLARIFICATIONS,
+		CONNECTION_PARAMETERS,
+		DYNAMIC_OUTPUT_NODES,
+		SUB_NODES_SEARCHES,
+		STRUCTURED_OUTPUT_PARSER,
+		CRITICAL_RULES,
+		RESTRICTIONS,
+	].join('\n\n');
+}

packages/@n8n/ai-workflow-builder.ee/src/prompts/agents/responder.prompt.ts

@@ -0,0 +1,45 @@
+/**
+ * Responder Agent Prompt
+ *
+ * Synthesizes final user-facing responses from workflow building context.
+ * Also handles conversational queries and explanations.
+ */
+
+const RESPONDER_ROLE = `You are a helpful AI assistant for n8n workflow automation.
+
+You have access to context about what has been built, including:
+- Discovery results (nodes found)
+- Builder output (workflow structure)
+- Configuration summary (setup instructions)`;
+
+const WORKFLOW_COMPLETION = `FOR WORKFLOW COMPLETION RESPONSES:
+When you receive [Internal Context], synthesize a clean user-facing response:
+1. Summarize what was built in a friendly way
+2. Explain the workflow structure briefly
+3. Include setup instructions if provided
+4. Ask if user wants adjustments
+
+Example response structure:
+"I've created your [workflow type] workflow! Here's what it does:
+[Brief explanation of the flow]
+
+**Setup Required:**
+[List any configuration steps from the context]
+
+Let me know if you'd like to adjust anything."`;
+
+const CONVERSATIONAL_RESPONSES = `FOR QUESTIONS/CONVERSATIONS:
+- Be friendly and concise
+- Explain n8n capabilities when asked
+- Provide practical examples when helpful`;
+
+const RESPONSE_STYLE = `RESPONSE STYLE:
+- Keep responses focused and not overly long
+- Use markdown formatting for readability
+- Be conversational and helpful`;
+
+export function buildResponderPrompt(): string {
+	return [RESPONDER_ROLE, WORKFLOW_COMPLETION, CONVERSATIONAL_RESPONSES, RESPONSE_STYLE].join(
+		'\n\n',
+	);
+}

packages/@n8n/ai-workflow-builder.ee/src/prompts/agents/supervisor.prompt.ts

@@ -0,0 +1,57 @@
+/**
+ * Supervisor Agent Prompt
+ *
+ * Handles INITIAL routing based on user intent.
+ * After initial routing, deterministic routing takes over based on coordination log.
+ */
+
+const SUPERVISOR_ROLE = 'You are a Supervisor that routes user requests to specialist agents.';
+
+const AVAILABLE_AGENTS = `AVAILABLE AGENTS:
+- discovery: Find n8n nodes for building/modifying workflows
+- builder: Create nodes and connections (requires discovery first for new node types)
+- configurator: Set parameters on EXISTING nodes (no structural changes)
+- responder: Answer questions, confirm completion (TERMINAL)`;
+
+const ROUTING_DECISION_TREE = `ROUTING DECISION TREE:
+
+1. Is user asking a question or chatting? → responder
+   Examples: "what does this do?", "explain the workflow", "thanks"
+
+2. Does the request involve NEW or DIFFERENT node types? → discovery
+   Examples:
+   - "Build a workflow that..." (new workflow)
+   - "Use [ServiceB] instead of [ServiceA]" (replacing node type)
+   - "Add [some integration]" (new integration)
+   - "Switch from [ServiceA] to [ServiceB]" (swapping services)
+
+3. Is the request about connecting/disconnecting existing nodes? → builder
+   Examples: "Connect node A to node B", "Remove the connection to X"
+
+4. Is the request about changing VALUES in existing nodes? → configurator
+   Examples:
+   - "Change the URL to https://..."
+   - "Set the timeout to 30 seconds"
+   - "Update the email subject to..."`;
+
+/** Clarifies replacement (discovery) vs configuration - common confusion point */
+const KEY_DISTINCTION = `KEY DISTINCTION:
+- "Use [ServiceB] instead of [ServiceA]" = REPLACEMENT = discovery (new node type needed)
+- "Change the [ServiceA] API key" = CONFIGURATION = configurator (same node, different value)`;
+
+const OUTPUT_FORMAT = `OUTPUT:
+- reasoning: One sentence explaining your routing decision
+- next: Agent name`;
+
+export function buildSupervisorPrompt(): string {
+	return [
+		SUPERVISOR_ROLE,
+		AVAILABLE_AGENTS,
+		ROUTING_DECISION_TREE,
+		KEY_DISTINCTION,
+		OUTPUT_FORMAT,
+	].join('\n\n');
+}
+
+export const SUPERVISOR_PROMPT_SUFFIX =
+	'\n\nGiven the conversation above, which agent should act next? Provide your reasoning and selection.';

packages/@n8n/ai-workflow-builder.ee/src/prompts/chains/categorization.prompt.ts

@@ -0,0 +1,91 @@
+import { PromptTemplate } from '@langchain/core/prompts';
+
+import { WorkflowTechnique, TechniqueDescription } from '@/types/categorization';
+
+/** Few-shot examples for prompt categorization - helps LLM understand expected output format */
+export const examplePrompts = [
+	{
+		prompt: 'Monitor social channels for product mentions and auto-respond with campaign messages',
+		techniques: [
+			WorkflowTechnique.MONITORING,
+			WorkflowTechnique.CHATBOT,
+			WorkflowTechnique.CONTENT_GENERATION,
+		],
+	},
+	{
+		prompt: 'Collect partner referral submissions and verify client instances via BigQuery',
+		techniques: [
+			WorkflowTechnique.FORM_INPUT,
+			WorkflowTechnique.HUMAN_IN_THE_LOOP,
+			WorkflowTechnique.NOTIFICATION,
+		],
+	},
+	{
+		prompt: 'Scrape competitor pricing pages weekly and generate a summary report of changes',
+		techniques: [
+			WorkflowTechnique.SCHEDULING,
+			WorkflowTechnique.SCRAPING_AND_RESEARCH,
+			WorkflowTechnique.DATA_EXTRACTION,
+			WorkflowTechnique.DATA_ANALYSIS,
+		],
+	},
+	{
+		prompt: 'Process uploaded PDF contracts to extract client details and update CRM records',
+		techniques: [
+			WorkflowTechnique.DOCUMENT_PROCESSING,
+			WorkflowTechnique.DATA_EXTRACTION,
+			WorkflowTechnique.DATA_TRANSFORMATION,
+			WorkflowTechnique.ENRICHMENT,
+		],
+	},
+	{
+		prompt: 'Build a searchable internal knowledge base from past support tickets',
+		techniques: [
+			WorkflowTechnique.DATA_TRANSFORMATION,
+			WorkflowTechnique.DATA_ANALYSIS,
+			WorkflowTechnique.KNOWLEDGE_BASE,
+		],
+	},
+];
+
+/** Formats example prompts as "prompt → techniques" for few-shot learning */
+export function formatExamplePrompts(): string {
+	return examplePrompts
+		.map((example) => `- ${example.prompt} → ${example.techniques.join(',')}`)
+		.join('\n');
+}
+
+/** Generates bullet list of all techniques with descriptions */
+export function formatTechniqueList(): string {
+	return Object.entries(TechniqueDescription)
+		.map(([key, description]) => `- **${key}**: ${description}`)
+		.join('\n');
+}
+
+/** Template for analyzing user prompts and identifying workflow techniques */
+export const promptCategorizationTemplate = PromptTemplate.fromTemplate(
+	`Analyze the following user prompt and identify the workflow techniques required to fulfill the request.
+Be specific and identify all relevant techniques.
+
+<user_prompt>
+{userPrompt}
+</user_prompt>
+
+<workflow_techniques>
+{techniques}
+</workflow_techniques>
+
+The following prompt categorization examples show a prompt → techniques involved to provide a sense
+of how the categorization should be carried out.
+<example_categorization>
+${formatExamplePrompts()}
+</example_categorization>
+
+Select a maximum of 5 techniques that you believe are applicable, but only select them if you are
+confident that they are applicable. If the prompt is ambiguous or does not provide an obvious workflow
+do not provide any techniques - if confidence is low avoid providing techniques.
+
+Select ALL techniques that apply to this workflow. Most workflows use multiple techniques.
+Rate your confidence in this categorization from 0.0 to 1.0.
+`,
+);

packages/@n8n/ai-workflow-builder.ee/src/prompts/chains/compact.prompt.ts

@@ -0,0 +1,16 @@
+import { PromptTemplate } from '@langchain/core/prompts';
+
+/** Template for summarizing multi-turn conversations into a structured format */
+export const compactPromptTemplate = PromptTemplate.fromTemplate(
+	`Please summarize the following conversation between a user and an AI assistant building an n8n workflow:
+
+<previous_summary>
+{previousSummary}
+</previous_summary>
+
+<conversation>
+{conversationText}
+</conversation>
+
+Provide a structured summary that captures the key points, decisions made, current state of the workflow, and suggested next steps.`,
+);

packages/@n8n/ai-workflow-builder.ee/src/prompts/chains/parameter-updater/index.ts

@@ -0,0 +1,26 @@
+export { ParameterUpdatePromptBuilder } from './prompt-builder';
+export { instanceUrlPrompt } from './instance-url';
+export {
+	DEFAULT_PROMPT_CONFIG,
+	getNodeTypeCategory,
+	mentionsResourceKeywords,
+	mentionsTextKeywords,
+} from './prompt-config';
+
+// Base prompts
+export { CORE_INSTRUCTIONS } from './base/core-instructions';
+export { EXPRESSION_RULES } from './base/expression-rules';
+export { COMMON_PATTERNS } from './base/common-patterns';
+export { OUTPUT_FORMAT } from './base/output-format';
+
+// Node type guides
+export { SET_NODE_GUIDE } from './node-types/set-node';
+export { IF_NODE_GUIDE } from './node-types/if-node';
+export { SWITCH_NODE_GUIDE } from './node-types/switch-node';
+export { HTTP_REQUEST_GUIDE } from './node-types/http-request';
+export { TOOL_NODES_GUIDE } from './node-types/tool-nodes';
+
+// Parameter type guides
+export { RESOURCE_LOCATOR_GUIDE } from './parameter-types/resource-locator';
+export { SYSTEM_MESSAGE_GUIDE } from './parameter-types/system-message';
+export { TEXT_FIELDS_GUIDE } from './parameter-types/text-fields';

packages/@n8n/ai-workflow-builder.ee/src/prompts/chains/parameter-updater/prompt-builder.ts

@@ -1,5 +1,7 @@
 import type { INodeTypeDescription, INodeProperties } from 'n8n-workflow';
 
+import type { PromptBuilderContext } from '@/types/config';
+
 import { COMMON_PATTERNS } from './base/common-patterns';
 import { CORE_INSTRUCTIONS } from './base/core-instructions';
 import { EXPRESSION_RULES } from './base/expression-rules';
@@ -23,7 +25,6 @@ import {
 	getNodeTypeCategory,
 	mentionsResourceKeywords,
 } from './prompt-config';
-import type { PromptBuilderContext } from '../../types/config';
 
 export class ParameterUpdatePromptBuilder {
 	/**

packages/@n8n/ai-workflow-builder.ee/src/prompts/chains/parameter-updater/prompt-config.ts

@@ -1,4 +1,4 @@
-import type { NodePromptConfig } from '../../types/config';
+import type { NodePromptConfig } from '@/types/config';
 
 export const DEFAULT_PROMPT_CONFIG: NodePromptConfig = {
 	nodeTypePatterns: {

packages/@n8n/ai-workflow-builder.ee/src/prompts/chains/workflow-name.prompt.ts

@@ -0,0 +1,13 @@
+import { PromptTemplate } from '@langchain/core/prompts';
+
+/** Template for generating descriptive workflow names from user prompts */
+export const workflowNamingPromptTemplate = PromptTemplate.fromTemplate(
+	`Based on the initial user prompt, please generate a name for the workflow that captures its essence and purpose.
+
+<initial_prompt>
+{initialPrompt}
+</initial_prompt>
+
+This name should be concise, descriptive, and suitable for a workflow that automates tasks related to the given prompt. The name should be in a format that is easy to read and understand. Do not include the word "workflow" in the name.
+`,
+);

packages/@n8n/ai-workflow-builder.ee/src/prompts/index.ts

@@ -0,0 +1,56 @@
+/**
+ * Centralized prompts for AI Workflow Builder
+ *
+ * This directory contains all prompts used by the AI workflow builder agents and chains.
+ * Organization:
+ * - agents/ - Multi-agent system prompts (builder, configurator, discovery, etc.)
+ * - chains/ - Chain-level prompts (categorization, compact, workflow-name, parameter-updater)
+ * - legacy-agent.prompt.ts - Legacy single-agent mode prompt
+ */
+
+// Agent prompts (multi-agent system)
+export { buildBuilderPrompt } from './agents/builder.prompt';
+export {
+	buildDiscoveryPrompt,
+	formatTechniqueList,
+	formatExampleCategorizations,
+	type DiscoveryPromptOptions,
+} from './agents/discovery.prompt';
+export { buildConfiguratorPrompt, INSTANCE_URL_PROMPT } from './agents/configurator.prompt';
+export { buildSupervisorPrompt, SUPERVISOR_PROMPT_SUFFIX } from './agents/supervisor.prompt';
+export { buildResponderPrompt } from './agents/responder.prompt';
+
+// Legacy agent prompt (single-agent mode)
+export {
+	createMainAgentPrompt,
+	mainAgentPrompt,
+	type MainAgentPromptOptions,
+} from './legacy-agent.prompt';
+
+// Chain prompts
+export {
+	promptCategorizationTemplate,
+	examplePrompts,
+	formatExamplePrompts,
+	formatTechniqueList as formatCategorizationTechniqueList,
+} from './chains/categorization.prompt';
+export { compactPromptTemplate } from './chains/compact.prompt';
+export { workflowNamingPromptTemplate } from './chains/workflow-name.prompt';
+
+// Parameter updater prompts
+export {
+	ParameterUpdatePromptBuilder,
+	instanceUrlPrompt,
+	CORE_INSTRUCTIONS,
+	EXPRESSION_RULES,
+	COMMON_PATTERNS,
+	OUTPUT_FORMAT,
+	SET_NODE_GUIDE,
+	IF_NODE_GUIDE,
+	SWITCH_NODE_GUIDE,
+	HTTP_REQUEST_GUIDE,
+	TOOL_NODES_GUIDE,
+	RESOURCE_LOCATOR_GUIDE,
+	SYSTEM_MESSAGE_GUIDE,
+	TEXT_FIELDS_GUIDE,
+} from './chains/parameter-updater';

packages/@n8n/ai-workflow-builder.ee/src/prompts/legacy-agent.prompt.ts

@@ -1,6 +1,6 @@
 import { ChatPromptTemplate } from '@langchain/core/prompts';
 
-import { instanceUrlPrompt } from '../../chains/prompts/instance-url';
+import { instanceUrlPrompt } from './chains/parameter-updater/instance-url';
 
 /**
  * Phase configuration for the workflow creation sequence

packages/@n8n/ai-workflow-builder.ee/src/subgraphs/builder.subgraph.ts

@@ -7,6 +7,7 @@ import type { Logger } from '@n8n/backend-common';
 import type { INodeTypeDescription } from 'n8n-workflow';
 
 import { LLMServiceError } from '@/errors';
+import { buildBuilderPrompt } from '@/prompts/agents/builder.prompt';
 import type { ChatPayload } from '@/workflow-builder-agent';
 
 import { BaseSubgraph } from './subgraph-interface';
@@ -34,234 +35,6 @@ import {
 	createStandardShouldContinue,
 } from '../utils/subgraph-helpers';
 
-/**
- * Builder Agent Prompt
- */
-const BUILDER_PROMPT = `You are a Builder Agent specialized in constructing n8n workflows.
-
-MANDATORY EXECUTION SEQUENCE:
-You MUST follow these steps IN ORDER. Do not skip any step.
-
-STEP 1: CREATE NODES
-- Call add_nodes for EVERY node needed based on discovery results
-- Create multiple nodes in PARALLEL for efficiency
-- Do NOT respond with text - START BUILDING immediately
-
-STEP 2: CONNECT NODES
-- Call connect_nodes for ALL required connections
-- Connect multiple node pairs in PARALLEL
-
-STEP 3: VALIDATE (REQUIRED)
-- After ALL nodes and connections are created, call validate_structure
-- This step is MANDATORY - you cannot finish without it
-- If validation finds issues (missing trigger, invalid connections), fix them and validate again
-- MAXIMUM 3 VALIDATION ATTEMPTS: After 3 calls to validate_structure, proceed to respond regardless of remaining issues
-
-STEP 4: RESPOND TO USER
-- Only after validation passes, provide your brief summary
-
-⚠️ NEVER respond to the user without calling validate_structure first ⚠️
-
-NODE CREATION:
-Each add_nodes call creates ONE node. You must provide:
-- nodeType: The exact type from discovery (e.g., "n8n-nodes-base.httpRequest")
-- name: Descriptive name (e.g., "Fetch Weather Data")
-- connectionParametersReasoning: Explain your thinking about connection parameters
-- connectionParameters: Parameters that affect connections (or {{}} if none needed)
-
-<workflow_configuration_node>
-Always include a Workflow Configuration node at the start of every workflow.
-
-The Workflow Configuration node (n8n-nodes-base.set) should be placed immediately after the trigger node and before all other processing nodes.
-
-Placement rules:
-- Add between trigger and first processing node
-- Connect: Trigger → Workflow Configuration → First processing node
-- Name it "Workflow Configuration"
-</workflow_configuration_node>
-
-<data_parsing_strategy>
-For AI-generated structured data, prefer Structured Output Parser nodes over Code nodes.
-For binary file data, use Extract From File node to extract content from files before processing.
-Use Code nodes only for custom business logic beyond parsing.
-
-STRUCTURED OUTPUT PARSER RULE:
-When Discovery results include Structured Output Parser:
-1. Create the Structured Output Parser node
-2. Set AI Agent's hasOutputParser: true in connectionParameters
-3. Connect: Structured Output Parser → AI Agent (ai_outputParser connection)
-</data_parsing_strategy>
-
-<proactive_design>
-Anticipate workflow needs:
-- IF nodes for conditional logic when multiple outcomes exist
-- Set nodes for data transformation between incompatible formats
-- Schedule Triggers for recurring tasks
-- Error handling for external service calls
-
-NEVER use Split In Batches nodes.
-</proactive_design>
-
-<node_defaults_warning>
-CRITICAL: NEVER RELY ON DEFAULT PARAMETER VALUES FOR CONNECTIONS
-
-Default values often hide connection inputs/outputs. You MUST explicitly configure parameters that affect connections:
-- Vector Store: Mode parameter affects available connections - always set explicitly (e.g., mode: "insert", "retrieve", "retrieve-as-tool")
-- AI Agent: hasOutputParser default may not match your workflow needs
-- Document Loader: textSplittingMode affects whether it accepts a text splitter input
-
-ALWAYS check node details and set connectionParameters explicitly.
-</node_defaults_warning>
-
-CONNECTION PARAMETERS EXAMPLES:
-- Static nodes (HTTP Request, Set, Code): reasoning="Static inputs/outputs", parameters={{}}
-- AI Agent with structured output: reasoning="hasOutputParser enables ai_outputParser input for Structured Output Parser", parameters={{ hasOutputParser: true }}
-- Vector Store insert: reasoning="Insert mode requires document input", parameters={{ mode: "insert" }}
-- Document Loader custom: reasoning="Custom mode enables text splitter input", parameters={{ textSplittingMode: "custom" }}
-- Switch with routing rules: reasoning="Switch needs N outputs, creating N rules.values entries with outputKeys", parameters={{ mode: "rules", rules: {{ values: [...] }} }} - see <switch_node_pattern> for full structure
-
-<structured_output_parser_guidance>
-WHEN TO SET hasOutputParser: true on AI Agent:
-- Discovery found Structured Output Parser node → MUST set hasOutputParser: true
-- AI output will be used in conditions (IF/Switch nodes checking $json.field)
-- AI output will be formatted/displayed (HTML emails, reports with specific sections)
-- AI output will be stored in database/data tables with specific fields
-- AI is classifying, scoring, or extracting specific data fields
-</structured_output_parser_guidance>
-
-<node_connections_understanding>
-n8n connections flow from SOURCE (output) to TARGET (input).
-
-Regular data flow: Source node output → Target node input
-Example: HTTP Request → Set (HTTP Request is source, Set is target)
-
-AI sub-nodes PROVIDE capabilities, making them the SOURCE:
-- OpenAI Chat Model → AI Agent [ai_languageModel]
-- Calculator Tool → AI Agent [ai_tool]
-- Window Buffer Memory → AI Agent [ai_memory]
-- Token Splitter → Default Data Loader [ai_textSplitter]
-- Default Data Loader → Vector Store [ai_document]
-- Embeddings OpenAI → Vector Store [ai_embedding]
-</node_connections_understanding>
-
-<agent_node_distinction>
-Distinguish between two different agent node types:
-
-1. **AI Agent** (@n8n/n8n-nodes-langchain.agent)
-   - Main workflow node that orchestrates AI tasks
-   - Use for: Primary AI logic, chatbots, autonomous workflows
-
-2. **AI Agent Tool** (@n8n/n8n-nodes-langchain.agentTool)
-   - Sub-node that acts as a tool for another AI Agent
-   - Use for: Multi-agent systems where one agent calls another
-
-Default assumption: When discovery results include "agent", use AI Agent
-unless explicitly specified as "agent tool" or "sub-agent".
-</agent_node_distinction>
-
-<rag_workflow_pattern>
-For RAG (Retrieval-Augmented Generation) workflows:
-
-Main data flow:
-- Data source (e.g., HTTP Request) → Vector Store [main connection]
-
-AI capability connections:
-- Document Loader → Vector Store [ai_document]
-- Embeddings → Vector Store [ai_embedding]
-- Text Splitter → Document Loader [ai_textSplitter]
-
-Common mistake to avoid:
-- NEVER connect Document Loader to main data outputs
-- Document Loader is an AI sub-node that gives Vector Store document processing capability
-</rag_workflow_pattern>
-
-<switch_node_pattern>
-For Switch nodes with multiple routing paths:
-- The number of outputs is determined by the number of entries in rules.values[]
-- You MUST create the rules.values[] array with placeholder entries for each output branch
-- Each entry needs: conditions structure (with empty leftValue/rightValue) + renameOutput: true + descriptive outputKey
-- Configurator will fill in the actual condition values later
-- Use descriptive node names like "Route by Amount" or "Route by Status"
-
-Example connectionParameters for 3-way routing:
-{{
-  "mode": "rules",
-  "rules": {{
-    "values": [
-      {{
-        "conditions": {{
-          "options": {{ "caseSensitive": true, "leftValue": "", "typeValidation": "strict" }},
-          "conditions": [{{ "leftValue": "", "rightValue": "", "operator": {{ "type": "string", "operation": "equals" }} }}],
-          "combinator": "and"
-        }},
-        "renameOutput": true,
-        "outputKey": "Output 1 Name"
-      }},
-      {{
-        "conditions": {{
-          "options": {{ "caseSensitive": true, "leftValue": "", "typeValidation": "strict" }},
-          "conditions": [{{ "leftValue": "", "rightValue": "", "operator": {{ "type": "string", "operation": "equals" }} }}],
-          "combinator": "and"
-        }},
-        "renameOutput": true,
-        "outputKey": "Output 2 Name"
-      }},
-      {{
-        "conditions": {{
-          "options": {{ "caseSensitive": true, "leftValue": "", "typeValidation": "strict" }},
-          "conditions": [{{ "leftValue": "", "rightValue": "", "operator": {{ "type": "string", "operation": "equals" }} }}],
-          "combinator": "and"
-        }},
-        "renameOutput": true,
-        "outputKey": "Output 3 Name"
-      }}
-    ]
-  }}
-}}
-</switch_node_pattern>
-
-<connection_type_examples>
-**Main Connections** (regular data flow):
-- Trigger → HTTP Request → Set → Email
-
-**AI Language Model Connections** (ai_languageModel):
-- OpenAI Chat Model → AI Agent
-
-**AI Tool Connections** (ai_tool):
-- Calculator Tool → AI Agent
-- AI Agent Tool → AI Agent (for multi-agent systems)
-
-**AI Document Connections** (ai_document):
-- Document Loader → Vector Store
-
-**AI Embedding Connections** (ai_embedding):
-- OpenAI Embeddings → Vector Store
-
-**AI Text Splitter Connections** (ai_textSplitter):
-- Token Text Splitter → Document Loader
-
-**AI Memory Connections** (ai_memory):
-- Window Buffer Memory → AI Agent
-
-**AI Vector Store in retrieve-as-tool mode** (ai_tool):
-- Vector Store → AI Agent
-</connection_type_examples>
-
-DO NOT:
-- Respond before calling validate_structure
-- Skip validation even if you think structure is correct
-- Add commentary between tool calls - execute tools silently
-- Configure node parameters (that's the Configurator Agent's job)
-- Search for nodes (that's the Discovery Agent's job)
-- Make assumptions about node types - use exactly what Discovery found
-
-RESPONSE FORMAT (only after validation):
-Provide ONE brief text message summarizing:
-- What nodes were added
-- How they're connected
-
-Example: "Created 4 nodes: Trigger → Weather → Image Generation → Email"`;
-
 /**
  * Builder Subgraph State
  */
@@ -337,7 +110,7 @@ export class BuilderSubgraph extends BaseSubgraph<
 				[
 					{
 						type: 'text',
-						text: BUILDER_PROMPT,
+						text: buildBuilderPrompt(),
 						cache_control: { type: 'ephemeral' },
 					},
 				],

packages/@n8n/ai-workflow-builder.ee/src/subgraphs/configurator.subgraph.ts

@@ -8,6 +8,7 @@ import type { Logger } from '@n8n/backend-common';
 import type { INodeTypeDescription } from 'n8n-workflow';
 
 import { LLMServiceError } from '@/errors';
+import { buildConfiguratorPrompt, INSTANCE_URL_PROMPT } from '@/prompts/agents/configurator.prompt';
 
 import { BaseSubgraph } from './subgraph-interface';
 import type { ParentGraphState } from '../parent-graph-state';
@@ -33,126 +34,6 @@ import {
 } from '../utils/subgraph-helpers';
 import type { ChatPayload } from '../workflow-builder-agent';
 
-/**
- * Configurator Agent Prompt
- */
-const CONFIGURATOR_PROMPT = `You are a Configurator Agent specialized in setting up n8n node parameters.
-
-MANDATORY EXECUTION SEQUENCE:
-You MUST follow these steps IN ORDER. Do not skip any step.
-
-STEP 1: CONFIGURE ALL NODES
-- Call update_node_parameters for EVERY node in the workflow
-- Configure multiple nodes in PARALLEL for efficiency
-- Do NOT respond with text - START CONFIGURING immediately
-
-STEP 2: VALIDATE (REQUIRED)
-- After ALL configurations complete, call validate_configuration
-- This step is MANDATORY - you cannot finish without it
-- If validation finds issues, fix them and validate again
-- MAXIMUM 3 VALIDATION ATTEMPTS: After 3 calls to validate_configuration, proceed to respond regardless of remaining issues
-
-STEP 3: RESPOND TO USER
-- Only after validation passes, provide your response
-
-NEVER respond to the user without calling validate_configuration first
-
-WORKFLOW JSON DETECTION:
-- You receive <current_workflow_json> in your context
-- If you see nodes in the workflow JSON, you MUST configure them IMMEDIATELY
-- Look at the workflow JSON, identify each node, and call update_node_parameters for ALL of them
-
-PARAMETER CONFIGURATION:
-Use update_node_parameters with natural language instructions:
-- "Set URL to https://api.example.com/weather"
-- "Add header Authorization: Bearer token"
-- "Set method to POST"
-- "Add field 'status' with value 'processed'"
-
-SPECIAL EXPRESSIONS FOR TOOL NODES:
-Tool nodes (types ending in "Tool") support $fromAI expressions:
-- "Set sendTo to ={{ $fromAI('to') }}"
-- "Set subject to ={{ $fromAI('subject') }}"
-- "Set message to ={{ $fromAI('message_html') }}"
-- "Set timeMin to ={{ $fromAI('After', '', 'string') }}"
-
-$fromAI syntax: ={{ $fromAI('key', 'description', 'type', defaultValue) }}
-- ONLY use in tool nodes (check node type ends with "Tool")
-- Use for dynamic values that AI determines at runtime
-- For regular nodes, use static values or standard expressions
-
-CRITICAL PARAMETERS TO ALWAYS SET:
-- HTTP Request: URL, method, headers (if auth needed)
-- Set node: Fields to set with values
-- Code node: The actual code to execute
-- IF node: Conditions to check
-- Switch node: Configure rules.values[] with conditions for each output branch (uses same filter structure as IF node)
-- Document Loader: dataType parameter ('binary' for files like PDF, 'json' for JSON data)
-- AI nodes: Prompts, models, configurations
-- Tool nodes: Use $fromAI for dynamic recipient/subject/message fields
-
-NEVER RELY ON DEFAULT VALUES:
-Defaults are traps that cause runtime failures. Examples:
-- Document Loader defaults to 'json' but MUST be 'binary' when processing files
-- HTTP Request defaults to GET but APIs often need POST
-- Vector Store mode affects available connections - set explicitly (retrieve-as-tool when using with AI Agent)
-
-<switch_node_configuration>
-Switch nodes require configuring rules.values[] array - each entry creates one output:
-
-Structure per rule:
-{{
-  "conditions": {{
-    "options": {{ "caseSensitive": true, "leftValue": "", "typeValidation": "strict" }},
-    "conditions": [
-      {{
-        "leftValue": "={{{{ $json.fieldName }}}}",
-        "rightValue": <value>,
-        "operator": {{ "type": "number|string", "operation": "lt|gt|equals|etc" }}
-      }}
-    ],
-    "combinator": "and"
-  }},
-  "renameOutput": true,
-  "outputKey": "Descriptive Label"
-}}
-
-For numeric ranges (e.g., $100-$1000):
-- Use TWO conditions with combinator: "and"
-- First: gte (greater than or equal)
-- Second: lte (less than or equal)
-
-Always set renameOutput: true and provide descriptive outputKey labels.
-</switch_node_configuration>
-
-<response_format>
-After validation passes, provide a concise summary:
-- List any placeholders requiring user configuration (e.g., "URL placeholder needs actual endpoint")
-- Note which nodes were configured and key settings applied
-- Keep it brief - this output is used for coordination with other LLM agents, not displayed directly to users
-</response_format>
-
-DO NOT:
-- Respond before calling validate_configuration
-- Skip validation even if you think configuration is correct
-- Add commentary between tool calls - execute tools silently`;
-
-/**
- * Instance URL prompt template
- */
-const INSTANCE_URL_PROMPT = `
-<instance_url>
-The n8n instance base URL is: {instanceUrl}
-
-This URL is essential for webhook nodes and chat triggers as it provides the base URL for:
-- Webhook URLs that external services need to call
-- Chat trigger URLs for conversational interfaces
-- Any node that requires the full instance URL to generate proper callback URLs
-
-When working with webhook or chat trigger nodes, use this URL as the base for constructing proper endpoint URLs.
-</instance_url>
-`;
-
 /**
  * Configurator Subgraph State
  */
@@ -243,7 +124,7 @@ export class ConfiguratorSubgraph extends BaseSubgraph<
 				[
 					{
 						type: 'text',
-						text: CONFIGURATOR_PROMPT,
+						text: buildConfiguratorPrompt(),
 					},
 					{
 						type: 'text',

packages/@n8n/ai-workflow-builder.ee/src/subgraphs/discovery.subgraph.ts

@@ -11,10 +11,10 @@ import { z } from 'zod';
 
 import { LLMServiceError } from '@/errors';
 import {
-	TechniqueDescription,
-	WorkflowTechnique,
-	type WorkflowTechniqueType,
-} from '@/types/categorization';
+	buildDiscoveryPrompt,
+	formatTechniqueList,
+	formatExampleCategorizations,
+} from '@/prompts/agents/discovery.prompt';
 import type { BuilderFeatureFlags } from '@/workflow-builder-agent';
 
 import { BaseSubgraph } from './subgraph-interface';
@@ -31,136 +31,6 @@ import { buildWorkflowSummary, createContextMessage } from '../utils/context-bui
 import { appendArrayReducer, nodeConfigurationsReducer } from '../utils/state-reducers';
 import { executeSubgraphTools, extractUserRequest } from '../utils/subgraph-helpers';
 
-/**
- * Example categorizations to guide technique selection
- * Expanded with diverse examples to improve accuracy
- */
-const exampleCategorizations: Array<{
-	prompt: string;
-	techniques: WorkflowTechniqueType[];
-}> = [
-	{
-		prompt: 'Monitor social channels for product mentions and auto-respond with campaign messages',
-		techniques: [
-			WorkflowTechnique.MONITORING,
-			WorkflowTechnique.CHATBOT,
-			WorkflowTechnique.CONTENT_GENERATION,
-		],
-	},
-	{
-		prompt: 'Collect partner referral submissions and verify client instances via BigQuery',
-		techniques: [
-			WorkflowTechnique.FORM_INPUT,
-			WorkflowTechnique.HUMAN_IN_THE_LOOP,
-			WorkflowTechnique.NOTIFICATION,
-		],
-	},
-	{
-		prompt: 'Scrape competitor pricing pages weekly and generate a summary report of changes',
-		techniques: [
-			WorkflowTechnique.SCHEDULING,
-			WorkflowTechnique.SCRAPING_AND_RESEARCH,
-			WorkflowTechnique.DATA_EXTRACTION,
-			WorkflowTechnique.DATA_ANALYSIS,
-		],
-	},
-	{
-		prompt: 'Process uploaded PDF contracts to extract client details and update CRM records',
-		techniques: [
-			WorkflowTechnique.DOCUMENT_PROCESSING,
-			WorkflowTechnique.DATA_EXTRACTION,
-			WorkflowTechnique.DATA_TRANSFORMATION,
-			WorkflowTechnique.ENRICHMENT,
-		],
-	},
-	{
-		prompt: 'Build a searchable internal knowledge base from past support tickets',
-		techniques: [
-			WorkflowTechnique.DATA_TRANSFORMATION,
-			WorkflowTechnique.DATA_ANALYSIS,
-			WorkflowTechnique.KNOWLEDGE_BASE,
-		],
-	},
-	// Additional examples to address common misclassifications
-	{
-		prompt: 'Create an AI agent that writes and sends personalized emails to leads',
-		techniques: [WorkflowTechnique.CONTENT_GENERATION, WorkflowTechnique.NOTIFICATION],
-	},
-	{
-		prompt:
-			'Fetch trending topics from Google Trends and Reddit, select the best ones, and create social posts',
-		techniques: [
-			WorkflowTechnique.SCRAPING_AND_RESEARCH,
-			WorkflowTechnique.TRIAGE,
-			WorkflowTechnique.CONTENT_GENERATION,
-		],
-	},
-	{
-		prompt:
-			'Trigger when a new contact is created in HubSpot and enrich their profile with LinkedIn data',
-		techniques: [WorkflowTechnique.MONITORING, WorkflowTechnique.ENRICHMENT],
-	},
-	{
-		prompt: 'Get stock prices from financial APIs and analyze volatility patterns',
-		techniques: [WorkflowTechnique.SCRAPING_AND_RESEARCH, WorkflowTechnique.DATA_ANALYSIS],
-	},
-	{
-		prompt: 'Generate video reels from templates and auto-post to social media on schedule',
-		techniques: [
-			WorkflowTechnique.SCHEDULING,
-			WorkflowTechnique.DOCUMENT_PROCESSING,
-			WorkflowTechnique.CONTENT_GENERATION,
-		],
-	},
-	{
-		prompt: 'Receive news from Telegram channels, filter relevant ones, and forward to my channel',
-		techniques: [
-			WorkflowTechnique.MONITORING,
-			WorkflowTechnique.TRIAGE,
-			WorkflowTechnique.NOTIFICATION,
-		],
-	},
-	{
-		prompt: 'Analyze YouTube video performance data and generate a weekly report',
-		techniques: [
-			WorkflowTechnique.SCRAPING_AND_RESEARCH,
-			WorkflowTechnique.DATA_ANALYSIS,
-			WorkflowTechnique.DATA_TRANSFORMATION,
-		],
-	},
-	{
-		prompt:
-			'Create a chatbot that answers questions using data from a Google Sheet as knowledge base',
-		techniques: [WorkflowTechnique.CHATBOT, WorkflowTechnique.KNOWLEDGE_BASE],
-	},
-	{
-		prompt: 'Form submission with file upload triggers document extraction and approval workflow',
-		techniques: [
-			WorkflowTechnique.FORM_INPUT,
-			WorkflowTechnique.DOCUMENT_PROCESSING,
-			WorkflowTechnique.HUMAN_IN_THE_LOOP,
-		],
-	},
-];
-
-/**
- * Format technique descriptions for prompt
- */
-function formatTechniqueList(): string {
-	return Object.entries(TechniqueDescription)
-		.map(([key, description]) => `- **${key}**: ${description}`)
-		.join('\n');
-}
-
-/**
- * Format example categorizations for prompt
- */
-function formatExampleCategorizations(): string {
-	return exampleCategorizations
-		.map((example) => `- ${example.prompt} → ${example.techniques.join(', ')}`)
-		.join('\n');
-}
-
 /**
  * Strict Output Schema for Discovery
  * Simplified to reduce token usage while maintaining utility for downstream subgraphs
@@ -193,191 +63,6 @@ const discoveryOutputSchema = z.object({
 		.describe('List of n8n nodes identified as necessary for the workflow'),
 });
 
-interface DiscoveryPromptOptions {
-	includeExamples: boolean;
-}
-
-/**
- * Generate the process steps with proper numbering
- */
-function generateProcessSteps(options: DiscoveryPromptOptions): string {
-	const { includeExamples } = options;
-
-	const steps: string[] = [
-		'**Analyze user prompt** - Extract services, models, and technologies mentioned',
-		'**Call get_best_practices** with identified techniques (internal context)',
-	];
-
-	if (includeExamples) {
-		steps.push('**Call get_workflow_examples** with search queries for mentioned services/models');
-	}
-
-	const examplesContext = includeExamples ? ', and examples' : '';
-	steps.push(
-		`**Identify workflow components** from user request, best practices${examplesContext}`,
-		'**Call search_nodes IN PARALLEL** for all components (e.g., "Gmail", "OpenAI", "Schedule")',
-		'**Call get_node_details IN PARALLEL** for ALL promising nodes (batch multiple calls)',
-		`**Extract node information** from each node_details response:
-   - Node name from <name> tag
-   - Version number from <version> tag (required - extract the number)
-   - Connection-changing parameters from <connections> section`,
-		'**Call submit_discovery_results** with complete nodesFound array',
-	);
-
-	return steps.map((step, index) => `${index + 1}. ${step}`).join('\n');
-}
-
-/**
- * Generate available tools list based on feature flags
- */
-function generateAvailableToolsList(options: DiscoveryPromptOptions): string {
-	const { includeExamples } = options;
-
-	const tools = [
-		'- get_best_practices: Retrieve best practices (internal context)',
-		'- search_nodes: Find n8n nodes by keyword',
-		'- get_node_details: Get complete node information including <connections>',
-	];
-
-	if (includeExamples) {
-		tools.push('- get_workflow_examples: Search for workflow examples as reference');
-	}
-
-	tools.push('- submit_discovery_results: Submit final results');
-
-	return tools.join('\n');
-}
-
-/**
- * Discovery Agent Prompt
- */
-function generateDiscoveryPrompt(options: DiscoveryPromptOptions): string {
-	const availableTools = generateAvailableToolsList(options);
-	const processSteps = generateProcessSteps(options);
-
-	return `You are a Discovery Agent for n8n AI Workflow Builder.
-
-YOUR ROLE: Identify relevant n8n nodes and their connection-changing parameters.
-
-AVAILABLE TOOLS:
-${availableTools}
-
-PROCESS:
-${processSteps}
-
-TECHNIQUE CATEGORIZATION:
-When calling get_best_practices, select techniques that match the user's workflow intent.
-
-<available_techniques>
-{techniques}
-</available_techniques>
-
-<example_categorizations>
-{exampleCategorizations}
-</example_categorizations>
-
-<technique_clarifications>
-Common distinctions to get right:
-- **NOTIFICATION vs CHATBOT**: Use NOTIFICATION when SENDING emails/messages/alerts (including to Telegram CHANNELS which are broadcast-only). Use CHATBOT only when RECEIVING and REPLYING to direct messages in a conversation.
-- **MONITORING**: Use when workflow TRIGGERS on external events (new record created, status changed, incoming webhook, new message in channel). NOT just scheduled runs.
-- **SCRAPING_AND_RESEARCH vs DATA_EXTRACTION**: Use SCRAPING when fetching from EXTERNAL sources (APIs, websites, social media). Use DATA_EXTRACTION for parsing INTERNAL data you already have.
-- **TRIAGE**: Use when SELECTING, PRIORITIZING, ROUTING, or QUALIFYING items (e.g., "pick the best", "route to correct team", "qualify leads").
-- **DOCUMENT_PROCESSING**: Use for ANY file handling - PDFs, images, videos, Excel, Google Sheets, audio files, file uploads in forms.
-- **HUMAN_IN_THE_LOOP**: Use when workflow PAUSES for human approval, review, signing documents, responding to polls, or any manual input before continuing.
-- **DATA_ANALYSIS**: Use when ANALYZING, CLASSIFYING, IDENTIFYING PATTERNS, or UNDERSTANDING data (e.g., "analyze outcomes", "learn from previous", "classify by type", "identify trends").
-- **KNOWLEDGE_BASE**: Use when storing/retrieving from a DATA SOURCE for Q&A - includes vector DBs, spreadsheets used as databases, document collections.
-- **DATA_TRANSFORMATION**: Use when CONVERTING data format, creating REPORTS/SUMMARIES from analyzed data, or restructuring output.
-</technique_clarifications>
-
-Technique selection rules:
-- Select ALL techniques that apply (most workflows use 2-4)
-- Maximum 5 techniques
-- Only select techniques you're confident apply
-
-CONNECTION-CHANGING PARAMETERS - CRITICAL RULES:
-
-A parameter is connection-changing ONLY IF it appears in <input> or <output> expressions within <node_details>.
-
-**How to identify:**
-1. Look at the <connections> section in node details
-2. Check if <input> or <output> uses expressions like: ={{...parameterName...}}
-3. If a parameter is referenced in these expressions, it IS connection-changing
-4. If a parameter is NOT in <input>/<output> expressions, it is NOT connection-changing
-
-**Example from AI Agent:**
-\`\`\`xml
-<input>={{...hasOutputParser, needsFallback...}}</input>
-\`\`\`
-→ hasOutputParser and needsFallback ARE connection-changing (they control which inputs appear)
-
-**Counter-example:**
-\`\`\`xml
-<properties>
-  <property name="promptType">...</property>  <!-- NOT in <input>/<output> -->
-  <property name="systemMessage">...</property>  <!-- NOT in <input>/<output> -->
-</properties>
-\`\`\`
-→ promptType and systemMessage are NOT connection-changing (they don't affect connections)
-
-**Common connection-changing parameters:**
-- Vector Store: mode (appears in <input>/<output> expressions)
-- AI Agent: hasOutputParser, needsFallback (appears in <input> expression)
-- Merge: numberInputs (appears in <input> expression)
-- Webhook: responseMode (appears in <output> expression)
-
-<dynamic_output_nodes>
-Some nodes have DYNAMIC outputs that depend on parameter values:
-
-**Switch Node** (n8n-nodes-base.switch):
-- When mode is "rules", the number of outputs equals the number of routing rules
-- Connection parameter: mode: "rules" - CRITICAL for enabling rule-based routing
-- Each rule in rules.values[] creates one output
-- The rules parameter uses the same filter structure as IF node conditions
-- ALWAYS flag mode as connection-changing with possibleValues: ["rules", "expression"]
-
-**Merge Node** (n8n-nodes-base.merge):
-- numberInputs parameter controls how many inputs the node accepts
-
-When you find these nodes, ALWAYS flag mode/numberInputs as connection-changing parameters with possibleValues.
-</dynamic_output_nodes>
-
-SUB-NODES SEARCHES:
-When searching for AI nodes, ALSO search for their required sub-nodes:
-- "AI Agent" → also search for "Chat Model", "Memory", "Output Parser"
-- "Basic LLM Chain" → also search for "Chat Model", "Output Parser"
-- "Vector Store" → also search for "Embeddings", "Document Loader"
-
-STRUCTURED OUTPUT PARSER - WHEN TO INCLUDE:
-Search for "Structured Output Parser" (@n8n/n8n-nodes-langchain.outputParserStructured) when:
-- AI output will be used programmatically (conditions, formatting, database storage, API calls)
-- AI needs to extract specific fields (e.g., score, category, priority, action items)
-- AI needs to classify/categorize data into defined categories
-- Downstream nodes need to access specific fields from AI response (e.g., $json.score, $json.category)
-- Output will be displayed in a formatted way (e.g., HTML email with specific sections)
-- Data needs validation against a schema before processing
-
-
-- Always use search_nodes to find the exact node names and versions - NEVER guess versions
-
-CRITICAL RULES:
-- NEVER ask clarifying questions
-- ALWAYS call get_best_practices first
-- THEN Call search_nodes to learn about available nodes and their inputs and outputs
-- FINALLY call get_node_details IN PARALLEL for speed to get more details about RELVANT node
-- ALWAYS extract version number from <version> tag in node details
-- NEVER guess node versions - always use search_nodes to find exact versions
-- ONLY flag connectionChangingParameters if they appear in <input> or <output> expressions
-- If no parameters appear in connection expressions, return empty array []
-- Output ONLY: nodesFound with {{ nodeName, version, reasoning, connectionChangingParameters }}
-
-DO NOT:
-- Output text commentary between tool calls
-- Include bestPractices or categorization in submit_discovery_results
-- Flag parameters that don't affect connections
-- Stop without calling submit_discovery_results
-`;
-}
-
 /**
  * Discovery Subgraph State
  */
@@ -476,7 +161,7 @@ export class DiscoverySubgraph extends BaseSubgraph<
 		});
 
 		// Generate prompt based on feature flags
-		const discoveryPrompt = generateDiscoveryPrompt({ includeExamples });
+		const discoveryPrompt = buildDiscoveryPrompt({ includeExamples });
 
 		// Create agent with tools bound (including submit tool)
 		const systemPrompt = ChatPromptTemplate.fromMessages([

packages/@n8n/ai-workflow-builder.ee/src/test/workflow-builder-agent.test.ts

@@ -31,7 +31,7 @@ jest.mock('@/tools/update-node-parameters.tool', () => ({
 jest.mock('@/tools/get-node-parameter.tool', () => ({
 	createGetNodeParameterTool: jest.fn().mockReturnValue({ tool: { name: 'get_node_parameter' } }),
 }));
-jest.mock('@/tools/prompts/main-agent.prompt', () => ({
+jest.mock('@/prompts/legacy-agent.prompt', () => ({
 	mainAgentPrompt: {
 		invoke: jest.fn().mockResolvedValue('mocked prompt'),
 	},
@@ -67,7 +67,7 @@ Object.defineProperty(global, 'crypto', {
 
 import { MAX_AI_BUILDER_PROMPT_LENGTH } from '@/constants';
 import { ValidationError } from '@/errors';
-import { createMainAgentPrompt } from '@/tools/prompts/main-agent.prompt';
+import { createMainAgentPrompt } from '@/prompts/legacy-agent.prompt';
 import type { StreamOutput } from '@/types/streaming';
 import { createStreamProcessor } from '@/utils/stream-processor';
 import {

packages/@n8n/ai-workflow-builder.ee/src/workflow-builder-agent.ts

@@ -1,6 +1,6 @@
 import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import type { ToolMessage } from '@langchain/core/messages';
-import { AIMessage, HumanMessage, RemoveMessage } from '@langchain/core/messages';
+import { AIMessage, HumanMessage, isAIMessage, RemoveMessage } from '@langchain/core/messages';
 import type { RunnableConfig } from '@langchain/core/runnables';
 import type { LangChainTracer } from '@langchain/core/tracers/tracer_langchain';
 import type { MemorySaver, StateSnapshot } from '@langchain/langgraph';
@@ -19,6 +19,7 @@ import {
 	MAX_AI_BUILDER_PROMPT_LENGTH,
 	MAX_INPUT_TOKENS,
 } from '@/constants';
+import { createMainAgentPrompt } from '@/prompts/legacy-agent.prompt';
 import { trimWorkflowJSON } from '@/utils/trim-workflow-context';
 
 import { conversationCompactChain } from './chains/conversation-compact';
@@ -27,7 +28,6 @@ import { LLMServiceError, ValidationError, WorkflowStateError } from './errors';
 import { createMultiAgentWorkflowWithSubgraphs } from './multi-agent-workflow-subgraphs';
 import { SessionManagerService } from './session-manager.service';
 import { getBuilderTools } from './tools/builder-tools';
-import { createMainAgentPrompt } from './tools/prompts/main-agent.prompt';
 import type { SimpleWorkflow } from './types/workflow';
 import {
 	applyCacheControlMarkers,
@@ -143,6 +143,8 @@ export interface WorkflowBuilderAgentConfig {
 	onGenerationSuccess?: () => Promise<void>;
 	/** Metadata to include in LangSmith traces */
 	runMetadata?: Record<string, unknown>;
+	/** Feature flags for enabling/disabling features */
+	featureFlags?: BuilderFeatureFlags;
 }
 
 export interface ExpressionValue {
@@ -287,7 +289,7 @@ export class WorkflowBuilderAgent {
 
 		const shouldContinue = ({ messages }: typeof WorkflowState.State) => {
 			const lastMessage = messages[messages.length - 1];
-			if (!(lastMessage instanceof AIMessage)) {
+			if (!lastMessage || !isAIMessage(lastMessage)) {
 				throw new WorkflowStateError('Expected last message to be generated by the AI agent');
 			}
 

packages/@n8n/api-types/src/dto/data-table/rename-data-table-column.dto.ts

@@ -0,0 +1,7 @@
+import { Z } from 'zod-class';
+
+import { dataTableColumnNameSchema } from '../../schemas/data-table.schema';
+
+export class RenameDataTableColumnDto extends Z.class({
+	name: dataTableColumnNameSchema,
+}) {}

packages/@n8n/api-types/src/dto/index.ts

@@ -99,6 +99,7 @@ export { CreateDataTableColumnDto } from './data-table/create-data-table-column.
 export { AddDataTableRowsDto } from './data-table/add-data-table-rows.dto';
 export { AddDataTableColumnDto } from './data-table/add-data-table-column.dto';
 export { MoveDataTableColumnDto } from './data-table/move-data-table-column.dto';
+export { RenameDataTableColumnDto } from './data-table/rename-data-table-column.dto';
 
 export {
 	OAuthClientResponseDto,

packages/@n8n/backend-test-utils/src/test-db.ts

@@ -87,7 +87,9 @@ type EntityName =
 	| 'AuthorizationCode'
 	| 'AccessToken'
 	| 'RefreshToken'
-	| 'UserConsent';
+	| 'UserConsent'
+	| 'DynamicCredentialEntry'
+	| 'DynamicCredentialResolver';
 
 /**
  * Truncate specific DB tables in a test DB.

packages/@n8n/config/src/configs/logging.config.ts

@@ -28,6 +28,7 @@ export const LOG_SCOPES = [
 	'chat-hub',
 	'breaking-changes',
 	'circuit-breaker',
+	'dynamic-credentials',
 ] as const;
 
 export type LogScope = (typeof LOG_SCOPES)[number];

packages/@n8n/db/src/migrations/common/1764689388394-AddDynamicCredentialEntryTable.ts

@@ -0,0 +1,31 @@
+import type { MigrationContext, ReversibleMigration } from '../migration-types';
+
+const tableName = 'dynamic_credential_entry';
+
+export class AddDynamicCredentialEntryTable1764689388394 implements ReversibleMigration {
+	async up({ schemaBuilder: { createTable, column } }: MigrationContext) {
+		await createTable(tableName)
+			.withColumns(
+				column('credential_id').varchar(16).primary.notNull,
+				column('subject_id').varchar(16).primary.notNull,
+				column('resolver_id').varchar(16).primary.notNull,
+				column('data').text.notNull,
+			)
+			.withTimestamps.withForeignKey('credential_id', {
+				tableName: 'credentials_entity',
+				columnName: 'id',
+				onDelete: 'CASCADE',
+			})
+			.withForeignKey('resolver_id', {
+				tableName: 'dynamic_credential_resolver',
+				columnName: 'id',
+				onDelete: 'CASCADE',
+			})
+			.withIndexOn(['subject_id'])
+			.withIndexOn(['resolver_id']);
+	}
+
+	async down({ schemaBuilder: { dropTable } }: MigrationContext) {
+		await dropTable(tableName);
+	}
+}

packages/@n8n/db/src/migrations/mysqldb/index.ts

@@ -121,6 +121,7 @@ import { CreateBinaryDataTable1763716655000 } from '../common/1763716655000-Crea
 import { CreateWorkflowPublishHistoryTable1764167920585 } from '../common/1764167920585-CreateWorkflowPublishHistoryTable';
 import { AddCreatorIdToProjectTable1764276827837 } from '../common/1764276827837-AddCreatorIdToProjectTable';
 import { CreateDynamicCredentialResolverTable1764682447000 } from '../common/1764682447000-CreateCredentialResolverTable';
+import { AddDynamicCredentialEntryTable1764689388394 } from '../common/1764689388394-AddDynamicCredentialEntryTable';
 import type { Migration } from '../migration-types';
 
 export const mysqlMigrations: Migration[] = [
@@ -247,4 +248,5 @@ export const mysqlMigrations: Migration[] = [
 	CreateWorkflowPublishHistoryTable1764167920585,
 	AddCreatorIdToProjectTable1764276827837,
 	CreateDynamicCredentialResolverTable1764682447000,
+	AddDynamicCredentialEntryTable1764689388394,
 ];

packages/@n8n/db/src/migrations/postgresdb/index.ts

@@ -121,6 +121,7 @@ import { CreateBinaryDataTable1763716655000 } from '../common/1763716655000-Crea
 import { CreateWorkflowPublishHistoryTable1764167920585 } from '../common/1764167920585-CreateWorkflowPublishHistoryTable';
 import { AddCreatorIdToProjectTable1764276827837 } from '../common/1764276827837-AddCreatorIdToProjectTable';
 import { CreateDynamicCredentialResolverTable1764682447000 } from '../common/1764682447000-CreateCredentialResolverTable';
+import { AddDynamicCredentialEntryTable1764689388394 } from '../common/1764689388394-AddDynamicCredentialEntryTable';
 import type { Migration } from '../migration-types';
 
 export const postgresMigrations: Migration[] = [
@@ -247,4 +248,5 @@ export const postgresMigrations: Migration[] = [
 	CreateWorkflowPublishHistoryTable1764167920585,
 	AddCreatorIdToProjectTable1764276827837,
 	CreateDynamicCredentialResolverTable1764682447000,
+	AddDynamicCredentialEntryTable1764689388394,
 ];

packages/@n8n/db/src/migrations/sqlite/index.ts

@@ -117,6 +117,7 @@ import { ChangeOAuthStateColumnToUnboundedVarchar1763572724000 } from '../common
 import { CreateBinaryDataTable1763716655000 } from '../common/1763716655000-CreateBinaryDataTable';
 import { CreateWorkflowPublishHistoryTable1764167920585 } from '../common/1764167920585-CreateWorkflowPublishHistoryTable';
 import { CreateDynamicCredentialResolverTable1764682447000 } from '../common/1764682447000-CreateCredentialResolverTable';
+import { AddDynamicCredentialEntryTable1764689388394 } from '../common/1764689388394-AddDynamicCredentialEntryTable';
 import type { Migration } from '../migration-types';
 
 const sqliteMigrations: Migration[] = [
@@ -239,6 +240,7 @@ const sqliteMigrations: Migration[] = [
 	CreateWorkflowPublishHistoryTable1764167920585,
 	AddCreatorIdToProjectTable1764276827837,
 	CreateDynamicCredentialResolverTable1764682447000,
+	AddDynamicCredentialEntryTable1764689388394,
 ];
 
 export { sqliteMigrations };

packages/@n8n/decorators/src/module/module.ts

@@ -16,13 +16,18 @@ export interface BaseEntity {
 	reload(): Promise<void>;
 }
 
-export interface TimestampedEntity {
+export interface TimestampedIdEntity {
 	id: string;
 	createdAt: Date;
 	updatedAt: Date;
 }
 
-export type EntityClass = new () => BaseEntity | TimestampedEntity;
+export interface TimestampedEntity {
+	createdAt: Date;
+	updatedAt: Date;
+}
+
+export type EntityClass = new () => BaseEntity | TimestampedIdEntity | TimestampedEntity;
 
 export type ModuleSettings = Record<string, unknown>;
 export type ModuleContext = Record<string, unknown>;

packages/@n8n/nodes-langchain/nodes/mcp/McpClientTool/__test__/McpClientTool.node.test.ts

@@ -292,7 +292,9 @@ describe('McpClientTool', () => {
 
 		it('should successfully execute a tool', async () => {
 			jest.spyOn(Client.prototype, 'connect').mockResolvedValue();
-			jest.spyOn(Client.prototype, 'callTool').mockResolvedValue({ content: 'Sunny' });
+			jest
+				.spyOn(Client.prototype, 'callTool')
+				.mockResolvedValue({ toolResult: 'Sunny', content: [] });
 			jest.spyOn(Client.prototype, 'listTools').mockResolvedValue({
 				tools: [
 					{
@@ -326,9 +328,11 @@ describe('McpClientTool', () => {
 
 		it('should handle tool errors', async () => {
 			jest.spyOn(Client.prototype, 'connect').mockResolvedValue();
-			jest
-				.spyOn(Client.prototype, 'callTool')
-				.mockResolvedValue({ isError: true, content: [{ text: 'Weather unknown at location' }] });
+			jest.spyOn(Client.prototype, 'callTool').mockResolvedValue({
+				isError: true,
+				toolResult: 'Weather unknown at location',
+				content: [{ text: 'Weather unknown at location' }],
+			});
 			jest.spyOn(Client.prototype, 'listTools').mockResolvedValue({
 				tools: [
 					{

packages/@n8n/nodes-langchain/nodes/mcp/shared/utils.ts

@@ -114,7 +114,7 @@ export async function connectMcpClient({
 		return createResultError({ type: 'invalid_url', error: endpoint.error });
 	}
 
-	const client = new Client({ name, version: version.toString() }, { capabilities: { tools: {} } });
+	const client = new Client({ name, version: version.toString() }, { capabilities: {} });
 
 	if (serverTransport === 'httpStreamable') {
 		try {

packages/@n8n/nodes-langchain/nodes/tools/ToolWorkflow/v2/utils/WorkflowToolService.ts

@@ -173,9 +173,13 @@ export class WorkflowToolService {
 
 						return processedResponse;
 					}
-
 					// If manualLogging is false we've been called by the engine and need
 					// the structured response.
+
+					if (metadata && 'setMetadata' in context) {
+						void context.setMetadata(metadata);
+					}
+
 					return responseData;
 				} catch (error) {
 					// Check if error is due to cancellation

packages/@n8n/nodes-langchain/package.json

@@ -203,7 +203,7 @@
     "@langchain/redis": "1.0.1",
     "@langchain/textsplitters": "1.0.1",
     "@langchain/weaviate": "1.0.1",
-    "@modelcontextprotocol/sdk": "1.20.0",
+    "@modelcontextprotocol/sdk": "1.24.0",
     "@mozilla/readability": "0.6.0",
     "@n8n/client-oauth2": "workspace:*",
     "@n8n/config": "workspace:*",

packages/@n8n/task-runner/src/start.ts

@@ -54,7 +54,15 @@ void (async function start() {
 	});
 
 	sentry = Container.get(TaskRunnerSentry);
-	await sentry.initIfEnabled();
+	try {
+		await sentry.initIfEnabled();
+	} catch (error) {
+		console.error(
+			'FAILED TO INITIALIZE SENTRY. ERROR REPORTING WILL BE DISABLED. THIS IS LIKELY A CONFIGURATION OR ENVIRONMENT ISSUE.',
+			error,
+		);
+		sentry = undefined;
+	}
 
 	runner = new JsTaskRunner(config);
 	runner.on('runner:reached-idle-timeout', () => {

packages/cli/src/auth/__tests__/auth.service.test.ts

@@ -6,6 +6,7 @@ import type {
 	InvalidAuthTokenRepository,
 	UserRepository,
 } from '@n8n/db';
+import { GLOBAL_OWNER_ROLE } from '@n8n/db';
 import type { NextFunction, Response } from 'express';
 import { mock } from 'jest-mock-extended';
 import jwt from 'jsonwebtoken';
@@ -15,6 +16,7 @@ import { AUTH_COOKIE_NAME } from '@/constants';
 import type { MfaService } from '@/mfa/mfa.service';
 import { JwtService } from '@/services/jwt.service';
 import type { UrlService } from '@/services/url.service';
+import type { License } from '@/license';
 
 describe('AuthService', () => {
 	const browserId = 'test-browser-id';
@@ -35,10 +37,11 @@ describe('AuthService', () => {
 	const userRepository = mock<UserRepository>();
 	const invalidAuthTokenRepository = mock<InvalidAuthTokenRepository>();
 	const mfaService = mock<MfaService>();
+	const license = mock<License>();
 	const authService = new AuthService(
 		globalConfig,
 		mock(),
-		mock(),
+		license,
 		jwtService,
 		urlService,
 		userRepository,
@@ -61,6 +64,7 @@ describe('AuthService', () => {
 		globalConfig.userManagement.jwtSessionDurationHours = 168;
 		globalConfig.userManagement.jwtRefreshTimeoutHours = 0;
 		globalConfig.auth.cookie = { secure: true, samesite: 'lax' };
+		license.isWithinUsersLimit.mockReturnValue(true);
 	});
 
 	describe('createJWTHash', () => {
@@ -520,6 +524,29 @@ describe('AuthService', () => {
 			});
 		});
 
+		describe('when user limit is reached', () => {
+			it('should block issuance if the user is not the global owner', async () => {
+				license.isWithinUsersLimit.mockReturnValue(false);
+				expect(() => {
+					authService.issueCookie(res, user, false, browserId);
+				}).toThrowError('Maximum number of users reached');
+			});
+
+			it('should allow issuance if the user is the global owner', async () => {
+				license.isWithinUsersLimit.mockReturnValue(false);
+				user.role = GLOBAL_OWNER_ROLE;
+				expect(() => {
+					authService.issueCookie(res, user, false, browserId);
+				}).not.toThrowError('Maximum number of users reached');
+				expect(res.cookie).toHaveBeenCalledWith('n8n-auth', validToken, {
+					httpOnly: true,
+					maxAge: 604800000,
+					sameSite: 'lax',
+					secure: true,
+				});
+			});
+		});
+
 		it('should issue a cookie with the correct options, when 2FA was used', () => {
 			authService.issueCookie(res, user, true, browserId);
 

packages/cli/src/auth/auth.service.ts

@@ -10,7 +10,6 @@ import type { NextFunction, Response } from 'express';
 import { JsonWebTokenError, TokenExpiredError } from 'jsonwebtoken';
 import type { StringValue as TimeUnitValue } from 'ms';
 
-import config from '@/config';
 import { AuthError } from '@/errors/response-errors/auth.error';
 import { ForbiddenError } from '@/errors/response-errors/forbidden.error';
 import { License } from '@/license';
@@ -171,11 +170,7 @@ export class AuthService {
 		// TODO: move this check to the login endpoint in AuthController
 		// If the instance has exceeded its user quota, prevent non-owners from logging in
 		const isWithinUsersLimit = this.license.isWithinUsersLimit();
-		if (
-			config.getEnv('userManagement.isInstanceOwnerSetUp') &&
-			user.role.slug !== GLOBAL_OWNER_ROLE.slug &&
-			!isWithinUsersLimit
-		) {
+		if (user.role.slug !== GLOBAL_OWNER_ROLE.slug && !isWithinUsersLimit) {
 			throw new ForbiddenError(RESPONSE_ERROR_MESSAGES.USERS_QUOTA_REACHED);
 		}
 

packages/cli/src/commands/user-management/reset.ts

@@ -3,7 +3,6 @@ import {
 	User,
 	CredentialsRepository,
 	ProjectRepository,
-	SettingsRepository,
 	SharedCredentialsRepository,
 	SharedWorkflowRepository,
 	UserRepository,
@@ -19,6 +18,7 @@ const defaultUserProps = {
 	lastName: null,
 	email: null,
 	password: null,
+	lastActiveAt: null,
 	role: 'global:owner',
 };
 
@@ -53,11 +53,6 @@ export class Reset extends BaseCommand {
 		);
 		await Container.get(SharedCredentialsRepository).save(newSharedCredentials);
 
-		await Container.get(SettingsRepository).update(
-			{ key: 'userManagement.isInstanceOwnerSetUp' },
-			{ value: 'false' },
-		);
-
 		this.logger.info('Successfully reset the database to default user state.');
 	}
 

packages/cli/src/config/schema.ts

@@ -7,10 +7,12 @@ import { Container } from '@n8n/di';
 export const schema = {
 	userManagement: {
 		/**
-		 * @important Do not remove until after cloud hooks are updated to stop using convict config.
+		 * @important Do not remove isInstanceOwnerSetUp until after cloud hooks (user-management) are updated to stop using
+		 * this property
+		 * @deprecated
 		 */
 		isInstanceOwnerSetUp: {
-			// n8n loads this setting from DB on startup
+			// n8n loads this setting from SettingsRepository (DB) on startup
 			doc: "Whether the instance owner's account has been set up",
 			format: Boolean,
 			default: false,

packages/cli/src/config/types.ts

@@ -76,7 +76,6 @@ type ToReturnType<T extends ConfigOptionPath> = T extends NumericPath
 type ExceptionPaths = {
 	'queue.bull.redis': RedisOptions;
 	processedDataManager: IProcessedDataConfig;
-	'userManagement.isInstanceOwnerSetUp': boolean;
 	'ui.banners.dismissed': string[] | undefined;
 	easyAIWorkflowOnboarded: boolean | undefined;
 };

packages/cli/src/controllers/__tests__/invitation.controller.test.ts

@@ -22,6 +22,7 @@ import { ForbiddenError } from '@/errors/response-errors/forbidden.error';
 import config from '@/config';
 import type { AuthlessRequest } from '@/requests';
 import { v4 as uuidv4 } from 'uuid';
+import { OwnershipService } from '@/services/ownership.service';
 
 describe('InvitationController', () => {
 	const logger: Logger = mockInstance(Logger);
@@ -33,22 +34,29 @@ describe('InvitationController', () => {
 	const userRepository: UserRepository = mockInstance(UserRepository);
 	const postHog: PostHogClient = mockInstance(PostHogClient);
 	const eventService: EventService = mockInstance(EventService);
+	const ownershipService: OwnershipService = mockInstance(OwnershipService);
+
+	function defaultInvitationController() {
+		return new InvitationController(
+			logger,
+			externalHooks,
+			authService,
+			userService,
+			license,
+			passwordUtility,
+			userRepository,
+			postHog,
+			eventService,
+			ownershipService,
+		);
+	}
 
 	describe('inviteUser', () => {
 		it('throws a BadRequestError if SSO is enabled', async () => {
 			jest.spyOn(ssoHelpers, 'isSsoCurrentAuthenticationMethod').mockReturnValue(true);
+			jest.spyOn(ownershipService, 'hasInstanceOwner').mockReturnValue(Promise.resolve(true));
 
-			const invitationController = new InvitationController(
-				logger,
-				externalHooks,
-				authService,
-				userService,
-				license,
-				passwordUtility,
-				userRepository,
-				postHog,
-				eventService,
-			);
+			const invitationController = defaultInvitationController();
 
 			const user = mock<User>({
 				id: '123',
@@ -77,18 +85,9 @@ describe('InvitationController', () => {
 		it('throws a ForbiddenError if the user limit quota has been reached', async () => {
 			jest.spyOn(ssoHelpers, 'isSsoCurrentAuthenticationMethod').mockReturnValue(false);
 			jest.spyOn(license, 'isWithinUsersLimit').mockReturnValue(false);
+			jest.spyOn(ownershipService, 'hasInstanceOwner').mockReturnValue(Promise.resolve(true));
 
-			const invitationController = new InvitationController(
-				logger,
-				externalHooks,
-				authService,
-				userService,
-				license,
-				passwordUtility,
-				userRepository,
-				postHog,
-				eventService,
-			);
+			const invitationController = defaultInvitationController();
 
 			const user = mock<User>({
 				id: '123',
@@ -112,18 +111,9 @@ describe('InvitationController', () => {
 			jest.spyOn(ssoHelpers, 'isSsoCurrentAuthenticationMethod').mockReturnValue(false);
 			jest.spyOn(license, 'isWithinUsersLimit').mockReturnValue(true);
 			jest.spyOn(config, 'getEnv').mockReturnValue(false);
+			jest.spyOn(ownershipService, 'hasInstanceOwner').mockReturnValue(Promise.resolve(false));
 
-			const invitationController = new InvitationController(
-				logger,
-				externalHooks,
-				authService,
-				userService,
-				license,
-				passwordUtility,
-				userRepository,
-				postHog,
-				eventService,
-			);
+			const invitationController = defaultInvitationController();
 
 			const user = mock<User>({
 				id: '123',
@@ -148,18 +138,9 @@ describe('InvitationController', () => {
 			jest.spyOn(license, 'isWithinUsersLimit').mockReturnValue(true);
 			jest.spyOn(config, 'getEnv').mockReturnValue(true);
 			jest.spyOn(license, 'isAdvancedPermissionsLicensed').mockReturnValue(false);
+			jest.spyOn(ownershipService, 'hasInstanceOwner').mockReturnValue(Promise.resolve(true));
 
-			const invitationController = new InvitationController(
-				logger,
-				externalHooks,
-				authService,
-				userService,
-				license,
-				passwordUtility,
-				userRepository,
-				postHog,
-				eventService,
-			);
+			const invitationController = defaultInvitationController();
 
 			const user = mock<User>({
 				id: '123',
@@ -209,17 +190,9 @@ describe('InvitationController', () => {
 			jest.spyOn(config, 'getEnv').mockReturnValue(true);
 			jest.spyOn(license, 'isAdvancedPermissionsLicensed').mockReturnValue(true);
 			jest.spyOn(userService, 'inviteUsers').mockResolvedValue(inviteUsersResult);
-			const invitationController = new InvitationController(
-				logger,
-				externalHooks,
-				authService,
-				userService,
-				license,
-				passwordUtility,
-				userRepository,
-				postHog,
-				eventService,
-			);
+			jest.spyOn(ownershipService, 'hasInstanceOwner').mockReturnValue(Promise.resolve(true));
+
+			const invitationController = defaultInvitationController();
 
 			const user = mock<User>({
 				id: '123',
@@ -255,19 +228,11 @@ describe('InvitationController', () => {
 	describe('acceptInvitation', () => {
 		it('throws a BadRequestError if SSO is enabled', async () => {
 			jest.spyOn(ssoHelpers, 'isSsoCurrentAuthenticationMethod').mockReturnValue(true);
+			jest.spyOn(ownershipService, 'hasInstanceOwner').mockReturnValue(Promise.resolve(true));
+
 			const id = uuidv4();
 
-			const invitationController = new InvitationController(
-				logger,
-				externalHooks,
-				authService,
-				userService,
-				license,
-				passwordUtility,
-				userRepository,
-				postHog,
-				eventService,
-			);
+			const invitationController = defaultInvitationController();
 
 			const payload = new AcceptInvitationRequestDto({
 				inviterId: id,
@@ -291,19 +256,11 @@ describe('InvitationController', () => {
 
 		it('throws a BadRequestError if the inviter ID and invitee ID are not found in the database', async () => {
 			jest.spyOn(ssoHelpers, 'isSsoCurrentAuthenticationMethod').mockReturnValue(false);
+			jest.spyOn(ownershipService, 'hasInstanceOwner').mockReturnValue(Promise.resolve(true));
+
 			const id = uuidv4();
 
-			const invitationController = new InvitationController(
-				logger,
-				externalHooks,
-				authService,
-				userService,
-				license,
-				passwordUtility,
-				userRepository,
-				postHog,
-				eventService,
-			);
+			const invitationController = defaultInvitationController();
 
 			const payload = new AcceptInvitationRequestDto({
 				inviterId: id,
@@ -332,6 +289,8 @@ describe('InvitationController', () => {
 
 		it('throws a BadRequestError if the invitee already has a password', async () => {
 			jest.spyOn(ssoHelpers, 'isSsoCurrentAuthenticationMethod').mockReturnValue(false);
+			jest.spyOn(ownershipService, 'hasInstanceOwner').mockReturnValue(Promise.resolve(true));
+
 			const invitee = mock<User>({
 				id: '123',
 				email: 'valid@email.com',
@@ -346,17 +305,7 @@ describe('InvitationController', () => {
 			jest.spyOn(userRepository, 'find').mockResolvedValue([inviter, invitee]);
 			const id = uuidv4();
 
-			const invitationController = new InvitationController(
-				logger,
-				externalHooks,
-				authService,
-				userService,
-				license,
-				passwordUtility,
-				userRepository,
-				postHog,
-				eventService,
-			);
+			const invitationController = defaultInvitationController();
 
 			const payload = new AcceptInvitationRequestDto({
 				inviterId: id,
@@ -379,6 +328,8 @@ describe('InvitationController', () => {
 
 		it('accepts the invitation successfully', async () => {
 			jest.spyOn(ssoHelpers, 'isSsoCurrentAuthenticationMethod').mockReturnValue(false);
+			jest.spyOn(ownershipService, 'hasInstanceOwner').mockReturnValue(Promise.resolve(true));
+
 			const id = uuidv4();
 			const inviter = mock<User>({
 				id: '124',
@@ -400,17 +351,7 @@ describe('InvitationController', () => {
 			jest.spyOn(userService, 'toPublic').mockResolvedValue(invitee as unknown as PublicUser);
 			jest.spyOn(externalHooks, 'run').mockResolvedValue(invitee as never);
 
-			const invitationController = new InvitationController(
-				logger,
-				externalHooks,
-				authService,
-				userService,
-				license,
-				passwordUtility,
-				userRepository,
-				postHog,
-				eventService,
-			);
+			const invitationController = defaultInvitationController();
 
 			const payload = new AcceptInvitationRequestDto({
 				inviterId: id,

packages/cli/src/controllers/__tests__/owner.controller.test.ts

@@ -1,103 +1,40 @@
-import type { DismissBannerRequestDto, OwnerSetupRequestDto } from '@n8n/api-types';
-import type { Logger } from '@n8n/backend-common';
-import {
-	type AuthenticatedRequest,
-	type User,
-	type PublicUser,
-	type SettingsRepository,
-	type UserRepository,
-	GLOBAL_OWNER_ROLE,
-} from '@n8n/db';
-import type { Response } from 'express';
+import type { DismissBannerRequestDto } from '@n8n/api-types';
 import { mock } from 'jest-mock-extended';
 
 import type { AuthService } from '@/auth/auth.service';
-import config from '@/config';
 import { OwnerController } from '@/controllers/owner.controller';
 import { BadRequestError } from '@/errors/response-errors/bad-request.error';
-import type { EventService } from '@/events/event.service';
 import type { BannerService } from '@/services/banner.service';
-import type { PasswordUtility } from '@/services/password.utility';
 import type { UserService } from '@/services/user.service';
+import type { OwnershipService } from '@/services/ownership.service';
+import type { PostHogClient } from '@/posthog';
 
 describe('OwnerController', () => {
-	const configGetSpy = jest.spyOn(config, 'getEnv');
-	const configSetSpy = jest.spyOn(config, 'set');
-
-	const logger = mock<Logger>();
-	const eventService = mock<EventService>();
 	const authService = mock<AuthService>();
 	const bannerService = mock<BannerService>();
 	const userService = mock<UserService>();
-	const userRepository = mock<UserRepository>();
-	const settingsRepository = mock<SettingsRepository>();
-	const passwordUtility = mock<PasswordUtility>();
+	const ownershipService = mock<OwnershipService>();
+	const postHogClient = mock<PostHogClient>();
 
 	const controller = new OwnerController(
-		logger,
-		eventService,
-		settingsRepository,
 		authService,
 		bannerService,
 		userService,
-		passwordUtility,
-		mock(),
-		userRepository,
+		postHogClient,
+		ownershipService,
 	);
 
 	describe('setupOwner', () => {
-		it('should throw a BadRequestError if the instance owner is already setup', async () => {
-			configGetSpy.mockReturnValue(true);
+		it('should pass on errors from the service', async () => {
+			jest
+				.spyOn(ownershipService, 'setupOwner')
+				.mockRejectedValueOnce(new BadRequestError('Instance owner already setup'));
+
 			await expect(controller.setupOwner(mock(), mock(), mock())).rejects.toThrowError(
 				new BadRequestError('Instance owner already setup'),
 			);
 
-			expect(userRepository.findOneOrFail).not.toHaveBeenCalled();
-			expect(userRepository.save).not.toHaveBeenCalled();
 			expect(authService.issueCookie).not.toHaveBeenCalled();
-			expect(settingsRepository.update).not.toHaveBeenCalled();
-			expect(configSetSpy).not.toHaveBeenCalled();
-			expect(eventService.emit).not.toHaveBeenCalled();
-			expect(logger.debug).toHaveBeenCalledWith(
-				'Request to claim instance ownership failed because instance owner already exists',
-			);
-		});
-
-		it('should setup the instance owner successfully', async () => {
-			const user = mock<User>({
-				id: 'userId',
-				role: GLOBAL_OWNER_ROLE,
-				authIdentities: [],
-			});
-			const browserId = 'test-browser-id';
-			const req = mock<AuthenticatedRequest>({ user, browserId, authInfo: { usedMfa: false } });
-			const res = mock<Response>();
-			const payload = mock<OwnerSetupRequestDto>({
-				email: 'valid@email.com',
-				password: 'NewPassword123',
-				firstName: 'Jane',
-				lastName: 'Doe',
-			});
-			configGetSpy.mockReturnValue(false);
-			userRepository.findOneOrFail.mockResolvedValue(user);
-			userRepository.save.mockResolvedValue(user);
-			userService.toPublic.mockResolvedValue(mock<PublicUser>({ id: 'newUserId' }));
-
-			const result = await controller.setupOwner(req, res, payload);
-
-			expect(userRepository.findOneOrFail).toHaveBeenCalledWith({
-				where: { role: { slug: GLOBAL_OWNER_ROLE.slug } },
-				relations: ['role'],
-			});
-			expect(userRepository.save).toHaveBeenCalledWith(user, { transaction: false });
-			expect(authService.issueCookie).toHaveBeenCalledWith(res, user, false, browserId);
-			expect(settingsRepository.update).toHaveBeenCalledWith(
-				{ key: 'userManagement.isInstanceOwnerSetUp' },
-				{ value: JSON.stringify(true) },
-			);
-			expect(configSetSpy).toHaveBeenCalledWith('userManagement.isInstanceOwnerSetUp', true);
-			expect(eventService.emit).toHaveBeenCalledWith('instance-owner-setup', { userId: 'userId' });
-			expect(result.id).toEqual('newUserId');
 		});
 	});
 

packages/cli/src/controllers/e2e.controller.ts

@@ -16,7 +16,6 @@ import { Request } from 'express';
 import { v4 as uuid } from 'uuid';
 
 import { ActiveWorkflowManager } from '@/active-workflow-manager';
-import config from '@/config';
 import { inE2ETests } from '@/constants';
 import { MessageEventBus } from '@/eventbus/message-event-bus/message-event-bus';
 import type { FeatureReturnType } from '@/license';
@@ -223,8 +222,7 @@ export class E2EController {
 
 	@Get('/env-feature-flags', { skipAuth: true })
 	async getEnvFeatureFlags() {
-		const currentFlags = this.frontendService.getSettings().envFeatureFlags;
-		return currentFlags;
+		return (await this.frontendService.getSettings()).envFeatureFlags;
 	}
 
 	@Patch('/env-feature-flags', { skipAuth: true })
@@ -254,7 +252,7 @@ export class E2EController {
 		}
 
 		// Return the current environment feature flags
-		const currentFlags = this.frontendService.getSettings().envFeatureFlags;
+		const currentFlags = (await this.frontendService.getSettings()).envFeatureFlags;
 		return {
 			success: true,
 			message: 'Environment feature flags updated',
@@ -364,13 +362,6 @@ export class E2EController {
 				mfaRecoveryCodes: encryptedRecoveryCodes,
 			});
 		}
-
-		await this.settingsRepo.update(
-			{ key: 'userManagement.isInstanceOwnerSetUp' },
-			{ value: 'true' },
-		);
-
-		config.set('userManagement.isInstanceOwnerSetUp', true);
 	}
 
 	private async resetCache() {

packages/cli/src/controllers/invitation.controller.ts

@@ -6,7 +6,6 @@ import { Post, GlobalScope, RestController, Body, Param } from '@n8n/decorators'
 import { Response } from 'express';
 
 import { AuthService } from '@/auth/auth.service';
-import config from '@/config';
 import { RESPONSE_ERROR_MESSAGES } from '@/constants';
 import { BadRequestError } from '@/errors/response-errors/bad-request.error';
 import { ForbiddenError } from '@/errors/response-errors/forbidden.error';
@@ -17,6 +16,7 @@ import { PostHogClient } from '@/posthog';
 import { AuthlessRequest } from '@/requests';
 import { PasswordUtility } from '@/services/password.utility';
 import { UserService } from '@/services/user.service';
+import { OwnershipService } from '@/services/ownership.service';
 import { isSsoCurrentAuthenticationMethod } from '@/sso.ee/sso-helpers';
 
 @RestController('/invitations')
@@ -31,6 +31,7 @@ export class InvitationController {
 		private readonly userRepository: UserRepository,
 		private readonly postHog: PostHogClient,
 		private readonly eventService: EventService,
+		private readonly ownershipService: OwnershipService,
 	) {}
 
 	/**
@@ -64,7 +65,7 @@ export class InvitationController {
 			throw new ForbiddenError(RESPONSE_ERROR_MESSAGES.USERS_QUOTA_REACHED);
 		}
 
-		if (!config.getEnv('userManagement.isInstanceOwnerSetUp')) {
+		if (!(await this.ownershipService.hasInstanceOwner())) {
 			this.logger.debug(
 				'Request to send email invite(s) to user(s) failed because the owner account is not set up',
 			);

packages/cli/src/controllers/oauth/__tests__/abstract-oauth.controller.test.ts

@@ -1,47 +0,0 @@
-import { shouldSkipAuthOnOAuthCallback } from '../abstract-oauth.controller';
-
-describe('shouldSkipAuthOnOAuthCallback', () => {
-	const originalEnv = process.env.N8N_SKIP_AUTH_ON_OAUTH_CALLBACK;
-
-	afterEach(() => {
-		// Restore original environment variable after each test
-		if (originalEnv === undefined) {
-			delete process.env.N8N_SKIP_AUTH_ON_OAUTH_CALLBACK;
-		} else {
-			process.env.N8N_SKIP_AUTH_ON_OAUTH_CALLBACK = originalEnv;
-		}
-	});
-
-	describe('when N8N_SKIP_AUTH_ON_OAUTH_CALLBACK is not set', () => {
-		beforeEach(() => {
-			delete process.env.N8N_SKIP_AUTH_ON_OAUTH_CALLBACK;
-		});
-
-		it('should return true', () => {
-			expect(shouldSkipAuthOnOAuthCallback()).toBe(false);
-		});
-	});
-
-	describe('with various environment variable values', () => {
-		const testCases = [
-			{ value: 'true', expected: true },
-			{ value: 'TRUE', expected: true },
-			{ value: 'True', expected: true },
-			{ value: 'false', expected: false },
-			{ value: 'FALSE', expected: false },
-			{ value: 'False', expected: false },
-			{ value: '', expected: false },
-			{ value: '1', expected: false },
-			{ value: 'yes', expected: false },
-			{ value: 'on', expected: false },
-			{ value: 'enabled', expected: false },
-			{ value: '   ', expected: false },
-			{ value: ' true ', expected: false },
-		] as const;
-
-		test.each(testCases)('"%s" value should return %s', ({ value, expected }) => {
-			process.env.N8N_SKIP_AUTH_ON_OAUTH_CALLBACK = value;
-			expect(shouldSkipAuthOnOAuthCallback()).toBe(expected);
-		});
-	});
-});

packages/cli/src/controllers/oauth/__tests__/oauth1-credential.controller.test.ts

@@ -1,57 +1,22 @@
 import { Logger } from '@n8n/backend-common';
 import { mockInstance } from '@n8n/backend-test-utils';
-import { Time } from '@n8n/constants';
-import type { CredentialsEntity, User } from '@n8n/db';
-import { CredentialsRepository, GLOBAL_OWNER_ROLE } from '@n8n/db';
+import { type CredentialsEntity, type User } from '@n8n/db';
 import { Container } from '@n8n/di';
-import Csrf from 'csrf';
+import { mock } from 'jest-mock-extended';
+import axios from 'axios';
 import type { Response } from 'express';
-import { captor, mock } from 'jest-mock-extended';
-import { Cipher, type InstanceSettings, ExternalSecretsProxy } from 'n8n-core';
-import type { IWorkflowExecuteAdditionalData } from 'n8n-workflow';
-import nock from 'nock';
-
 import { OAuth1CredentialController } from '@/controllers/oauth/oauth1-credential.controller';
-import { CredentialsFinderService } from '@/credentials/credentials-finder.service';
-import { CredentialsHelper } from '@/credentials-helper';
-import { VariablesService } from '@/environments.ee/variables/variables.service.ee';
-import { BadRequestError } from '@/errors/response-errors/bad-request.error';
-import { NotFoundError } from '@/errors/response-errors/not-found.error';
-import { ExternalHooks } from '@/external-hooks';
 import type { OAuthRequest } from '@/requests';
-import * as WorkflowExecuteAdditionalData from '@/workflow-execute-additional-data';
+import { OauthService } from '@/oauth/oauth.service';
+import { ExternalHooks } from '@/external-hooks';
 
-jest.mock('@/workflow-execute-additional-data');
+jest.mock('axios');
 
 describe('OAuth1CredentialController', () => {
+	const oauthService = mockInstance(OauthService);
+
 	mockInstance(Logger);
 	mockInstance(ExternalHooks);
-	mockInstance(ExternalSecretsProxy);
-	mockInstance(VariablesService, {
-		getAllCached: async () => [],
-	});
-	const additionalData = mock<IWorkflowExecuteAdditionalData>();
-	(WorkflowExecuteAdditionalData.getBase as jest.Mock).mockReturnValue(additionalData);
-
-	const cipher = new Cipher(mock<InstanceSettings>({ encryptionKey: 'password' }));
-	Container.set(Cipher, cipher);
-	const credentialsHelper = mockInstance(CredentialsHelper);
-	const credentialsRepository = mockInstance(CredentialsRepository);
-	const credentialsFinderService = mockInstance(CredentialsFinderService);
-
-	const csrfSecret = 'csrf-secret';
-	const user = mock<User>({
-		id: '123',
-		password: 'password',
-		authIdentities: [],
-		role: GLOBAL_OWNER_ROLE,
-	});
-	const credential = mock<CredentialsEntity>({
-		id: '1',
-		name: 'Test Credential',
-		type: 'oAuth1Api',
-		data: cipher.encrypt({}),
-	});
 
 	const controller = Container.get(OAuth1CredentialController);
 
@@ -64,64 +29,26 @@ describe('OAuth1CredentialController', () => {
 	});
 
 	describe('getAuthUri', () => {
-		it('should throw a BadRequestError when credentialId is missing in the query', async () => {
-			const req = mock<OAuthRequest.OAuth1Credential.Auth>({ query: { id: '' } });
-			await expect(controller.getAuthUri(req)).rejects.toThrowError(
-				new BadRequestError('Required credential ID is missing'),
-			);
-		});
-
-		it('should throw a NotFoundError when no matching credential is found for the user', async () => {
-			credentialsFinderService.findCredentialForUser.mockResolvedValueOnce(null);
-
-			const req = mock<OAuthRequest.OAuth1Credential.Auth>({ user, query: { id: '1' } });
-			await expect(controller.getAuthUri(req)).rejects.toThrowError(
-				new NotFoundError('Credential not found'),
-			);
-		});
-
 		it('should return a valid auth URI', async () => {
-			jest.spyOn(Csrf.prototype, 'secretSync').mockReturnValueOnce(csrfSecret);
-			jest.spyOn(Csrf.prototype, 'create').mockReturnValueOnce('token');
-			credentialsFinderService.findCredentialForUser.mockResolvedValueOnce(credential);
-			credentialsHelper.getDecrypted.mockResolvedValueOnce({});
-			credentialsHelper.applyDefaultsAndOverwrites.mockResolvedValueOnce({
+			const mockResolvedCredential = mock<CredentialsEntity>({ id: '1' });
+			oauthService.getCredential.mockResolvedValueOnce(mockResolvedCredential);
+			oauthService.createCsrfState.mockReturnValueOnce(['csrf-secret', 'state']);
+			oauthService.getOAuthCredentials.mockResolvedValueOnce({
 				requestTokenUrl: 'https://example.domain/oauth/request_token',
 				authUrl: 'https://example.domain/oauth/authorize',
 				accessTokenUrl: 'https://example.domain/oauth/access_token',
-				signatureMethod: 'HMAC-SHA1',
+				signatureMethod: 'HMAC-SHA1' as const,
+			});
+			jest.mocked(axios).request.mockResolvedValueOnce({ data: { oauth_token: 'random-token' } });
+			const req = mock<OAuthRequest.OAuth1Credential.Auth>({
+				user: mock<User>({ id: '123' }),
+				query: { id: '1' },
 			});
-			nock('https://example.domain')
-				.post('/oauth/request_token', {
-					oauth_callback:
-						'http://localhost:5678/rest/oauth1-credential/callback?state=eyJ0b2tlbiI6InRva2VuIiwiY2lkIjoiMSIsImNyZWF0ZWRBdCI6MTcwNjc1MDYyNTY3OCwidXNlcklkIjoiMTIzIn0=',
-				})
-				.once()
-				.reply(200, { oauth_token: 'random-token' });
-
-			const req = mock<OAuthRequest.OAuth1Credential.Auth>({ user, query: { id: '1' } });
 			const authUri = await controller.getAuthUri(req);
 			expect(authUri).toEqual('https://example.domain/oauth/authorize?oauth_token=random-token');
-			const dataCaptor = captor();
-			expect(credentialsRepository.update).toHaveBeenCalledWith(
-				'1',
-				expect.objectContaining({
-					data: dataCaptor,
-					id: '1',
-					name: 'Test Credential',
-					type: 'oAuth1Api',
-				}),
-			);
-			expect(cipher.decrypt(dataCaptor.value)).toEqual(
-				JSON.stringify({ csrfSecret: 'csrf-secret' }),
-			);
-			expect(credentialsHelper.getDecrypted).toHaveBeenCalledWith(
-				additionalData,
-				credential,
-				credential.type,
-				'internal',
-				undefined,
-				false,
+			expect(oauthService.encryptAndSaveData).toHaveBeenCalledWith(
+				mockResolvedCredential,
+				expect.objectContaining({ csrfSecret: 'csrf-secret' }),
 			);
 		});
 	});
@@ -149,113 +76,40 @@ describe('OAuth1CredentialController', () => {
 			invalidReq.query = { state: 'test' } as OAuthRequest.OAuth1Credential.Callback['query'];
 			await controller.handleCallback(invalidReq, res);
 
-			expect(res.render).toHaveBeenCalledWith('oauth-error-callback', {
-				error: {
-					message: 'Insufficient parameters for OAuth1 callback.',
-					reason: 'Received following query parameters: {"state":"test"}',
-				},
-			});
-			expect(credentialsRepository.findOneBy).not.toHaveBeenCalled();
-		});
-
-		it('should render the error page when `state` query param is invalid', async () => {
-			const invalidReq = mock<OAuthRequest.OAuth1Credential.Callback>({
-				query: {
-					oauth_verifier: 'verifier',
-					oauth_token: 'token',
-					state: 'test',
-				},
-			});
-			await controller.handleCallback(invalidReq, res);
-
-			expect(res.render).toHaveBeenCalledWith('oauth-error-callback', {
-				error: {
-					message: 'Invalid state format',
-				},
-			});
-			expect(credentialsRepository.findOneBy).not.toHaveBeenCalled();
-		});
-
-		it('should render the error page when credential is not found in DB', async () => {
-			credentialsRepository.findOneBy.mockResolvedValueOnce(null);
-
-			await controller.handleCallback(req, res);
-
-			expect(res.render).toHaveBeenCalledWith('oauth-error-callback', {
-				error: {
-					message: 'OAuth callback failed because of insufficient permissions',
-				},
-			});
-			expect(credentialsRepository.findOneBy).toHaveBeenCalledTimes(1);
-			expect(credentialsRepository.findOneBy).toHaveBeenCalledWith({ id: '1' });
-		});
-
-		it('should render the error page when state differs from the stored state in the credential', async () => {
-			credentialsRepository.findOneBy.mockResolvedValue(credential);
-			credentialsHelper.getDecrypted.mockResolvedValue({ csrfSecret: 'invalid' });
-
-			await controller.handleCallback(req, res);
-
-			expect(res.render).toHaveBeenCalledWith('oauth-error-callback', {
-				error: {
-					message: 'The OAuth callback state is invalid!',
-				},
-			});
-		});
-
-		it('should render the error page when state is older than 5 minutes', async () => {
-			credentialsRepository.findOneBy.mockResolvedValue(credential);
-			credentialsHelper.getDecrypted.mockResolvedValue({ csrfSecret });
-			jest.spyOn(Csrf.prototype, 'verify').mockReturnValueOnce(true);
-
-			jest.advanceTimersByTime(10 * Time.minutes.toMilliseconds);
-
-			await controller.handleCallback(req, res);
-
-			expect(res.render).toHaveBeenCalledWith('oauth-error-callback', {
-				error: {
-					message: 'The OAuth callback state is invalid!',
-				},
-			});
+			expect(oauthService.renderCallbackError).toHaveBeenCalledWith(
+				res,
+				'Insufficient parameters for OAuth1 callback.',
+				'Received following query parameters: {"state":"test"}',
+			);
 		});
 
 		it('should exchange the code for a valid token, and save it to DB', async () => {
-			credentialsRepository.findOneBy.mockResolvedValue(credential);
-			credentialsHelper.getDecrypted.mockResolvedValue({ csrfSecret });
-			credentialsHelper.applyDefaultsAndOverwrites.mockResolvedValueOnce({
+			const mockResolvedCredential = mock<CredentialsEntity>({ id: '1' });
+			oauthService.getCredential.mockResolvedValueOnce(mockResolvedCredential);
+			// @ts-ignore
+			oauthService.getDecryptedData.mockResolvedValue({ csrfSecret: 'invalid' });
+			oauthService.getOAuthCredentials.mockResolvedValueOnce({
 				requestTokenUrl: 'https://example.domain/oauth/request_token',
 				accessTokenUrl: 'https://example.domain/oauth/access_token',
 				signatureMethod: 'HMAC-SHA1',
 			});
-			jest.spyOn(Csrf.prototype, 'verify').mockReturnValueOnce(true);
-			nock('https://example.domain')
-				.post('/oauth/access_token', 'oauth_token=token&oauth_verifier=verifier')
-				.once()
-				.reply(200, 'access_token=new_token');
+			oauthService.resolveCredential.mockResolvedValueOnce([
+				mockResolvedCredential,
+				{ csrfSecret: 'invalid' },
+				{ accessTokenUrl: 'https://example.domain/oauth/access_token' },
+			]);
+			jest.mocked(axios).post.mockResolvedValueOnce({ data: { access_token: 'new_token' } });
 
 			await controller.handleCallback(req, res);
-			const dataCaptor = captor();
-			expect(credentialsRepository.update).toHaveBeenCalledWith(
-				'1',
+			// @ts-ignore
+			expect(oauthService.encryptAndSaveData).toHaveBeenCalledWith(
+				mockResolvedCredential,
 				expect.objectContaining({
-					data: dataCaptor,
-					id: '1',
-					name: 'Test Credential',
-					type: 'oAuth1Api',
+					oauthTokenData: { access_token: 'new_token' },
 				}),
-			);
-			expect(cipher.decrypt(dataCaptor.value)).toEqual(
-				JSON.stringify({ oauthTokenData: { access_token: 'new_token' } }),
+				['csrfSecret'],
 			);
 			expect(res.render).toHaveBeenCalledWith('oauth-callback');
-			expect(credentialsHelper.getDecrypted).toHaveBeenCalledWith(
-				additionalData,
-				credential,
-				credential.type,
-				'internal',
-				undefined,
-				true,
-			);
 		});
 	});
 });

packages/cli/src/controllers/oauth/oauth1-credential.controller.ts

@@ -9,7 +9,9 @@ import clientOAuth1 from 'oauth-1.0a';
 
 import { OAuthRequest } from '@/requests';
 
-import { AbstractOAuthController, skipAuthOnOAuthCallback } from './abstract-oauth.controller';
+import { OauthService, OauthVersion, skipAuthOnOAuthCallback } from '@/oauth/oauth.service';
+import { Logger } from '@n8n/backend-common';
+import { ExternalHooks } from '@/external-hooks';
 
 interface OAuth1CredentialData {
 	signatureMethod: 'HMAC-SHA256' | 'HMAC-SHA512' | 'HMAC-SHA1';
@@ -27,24 +29,24 @@ const algorithmMap = {
 } as const;
 
 @RestController('/oauth1-credential')
-export class OAuth1CredentialController extends AbstractOAuthController {
-	override oauthVersion = 1;
+export class OAuth1CredentialController {
+	constructor(
+		private readonly oauthService: OauthService,
+		private readonly externalHooks: ExternalHooks,
+		private readonly logger: Logger,
+	) {}
 
 	/** Get Authorization url */
 	@Get('/auth')
 	async getAuthUri(req: OAuthRequest.OAuth1Credential.Auth): Promise<string> {
-		const credential = await this.getCredential(req);
-		const additionalData = await this.getAdditionalData();
-		const decryptedDataOriginal = await this.getDecryptedDataForAuthUri(credential, additionalData);
-		const oauthCredentials = await this.applyDefaultsAndOverwrites<OAuth1CredentialData>(
-			credential,
-			decryptedDataOriginal,
-			additionalData,
-		);
-		const [csrfSecret, state] = this.createCsrfState(
-			credential.id,
-			skipAuthOnOAuthCallback ? undefined : req.user.id,
-		);
+		const credential = await this.oauthService.getCredential(req);
+		const oauthCredentials =
+			await this.oauthService.getOAuthCredentials<OAuth1CredentialData>(credential);
+
+		const [csrfSecret, state] = this.oauthService.createCsrfState({
+			cid: credential.id,
+			userId: skipAuthOnOAuthCallback ? undefined : req.user.id,
+		});
 
 		const signatureMethod = oauthCredentials.signatureMethod;
 
@@ -62,7 +64,7 @@ export class OAuth1CredentialController extends AbstractOAuthController {
 		};
 
 		const oauthRequestData = {
-			oauth_callback: `${this.baseUrl}/callback?state=${state}`,
+			oauth_callback: `${this.oauthService.getBaseUrl(OauthVersion.V1)}/callback?state=${state}`,
 		};
 
 		await this.externalHooks.run('oauth1.authenticate', [oAuthOptions, oauthRequestData]);
@@ -91,7 +93,7 @@ export class OAuth1CredentialController extends AbstractOAuthController {
 
 		const returnUri = `${oauthCredentials.authUrl}?oauth_token=${responseJson.oauth_token}`;
 
-		await this.encryptAndSaveData(credential, { csrfSecret });
+		await this.oauthService.encryptAndSaveData(credential, { csrfSecret });
 
 		this.logger.debug('OAuth1 authorization successful for new credential', {
 			userId: req.user.id,
@@ -108,7 +110,7 @@ export class OAuth1CredentialController extends AbstractOAuthController {
 			const { oauth_verifier, oauth_token, state: encodedState } = req.query;
 
 			if (!oauth_verifier || !oauth_token || !encodedState) {
-				return this.renderCallbackError(
+				return this.oauthService.renderCallbackError(
 					res,
 					'Insufficient parameters for OAuth1 callback.',
 					`Received following query parameters: ${JSON.stringify(req.query)}`,
@@ -116,7 +118,7 @@ export class OAuth1CredentialController extends AbstractOAuthController {
 			}
 
 			const [credential, _, oauthCredentials] =
-				await this.resolveCredential<OAuth1CredentialData>(req);
+				await this.oauthService.resolveCredential<OAuth1CredentialData>(req);
 
 			// Form URL encoded body https://datatracker.ietf.org/doc/html/rfc5849#section-3.5.2
 			const oauthToken = await axios.post<string>(
@@ -131,15 +133,18 @@ export class OAuth1CredentialController extends AbstractOAuthController {
 
 			const oauthTokenData = Object.fromEntries(paramParser.entries());
 
-			await this.encryptAndSaveData(credential, { oauthTokenData }, ['csrfSecret']);
+			console.log('oauthTokenData', oauthTokenData);
+
+			await this.oauthService.encryptAndSaveData(credential, { oauthTokenData }, ['csrfSecret']);
 
 			this.logger.debug('OAuth1 callback successful for new credential', {
 				credentialId: credential.id,
 			});
 			return res.render('oauth-callback');
 		} catch (e) {
+			console.log('error', e);
 			const error = ensureError(e);
-			return this.renderCallbackError(
+			return this.oauthService.renderCallbackError(
 				res,
 				error.message,
 				'body' in error ? jsonStringify(error.body) : undefined,

packages/cli/src/controllers/oauth/oauth2-credential.controller.ts

@@ -20,44 +20,31 @@ import {
 import pkceChallenge from 'pkce-challenge';
 import * as qs from 'querystring';
 
-import { AbstractOAuthController, skipAuthOnOAuthCallback } from './abstract-oauth.controller';
 import {
 	oAuthAuthorizationServerMetadataSchema,
 	dynamicClientRegistrationResponseSchema,
 } from './oauth2-dynamic-client-registration.schema';
 
-import { GENERIC_OAUTH2_CREDENTIALS_WITH_EDITABLE_SCOPE as GENERIC_OAUTH2_CREDENTIALS_WITH_EDITABLE_SCOPE } from '@/constants';
 import { BadRequestError } from '@/errors/response-errors/bad-request.error';
 import { OAuthRequest } from '@/requests';
+import { OauthService, OauthVersion, skipAuthOnOAuthCallback } from '@/oauth/oauth.service';
+import { Logger } from '@n8n/backend-common';
+import { ExternalHooks } from '@/external-hooks';
 
 @RestController('/oauth2-credential')
-export class OAuth2CredentialController extends AbstractOAuthController {
-	override oauthVersion = 2;
+export class OAuth2CredentialController {
+	constructor(
+		private readonly oauthService: OauthService,
+		private readonly logger: Logger,
+		private readonly externalHooks: ExternalHooks,
+	) {}
 
 	/** Get Authorization url */
 	@Get('/auth')
 	async getAuthUri(req: OAuthRequest.OAuth2Credential.Auth): Promise<string> {
-		const credential = await this.getCredential(req);
-		const additionalData = await this.getAdditionalData();
-		const decryptedDataOriginal = await this.getDecryptedDataForAuthUri(credential, additionalData);
-
-		// At some point in the past we saved hidden scopes to credentials (but shouldn't)
-		// Delete scope before applying defaults to make sure new scopes are present on reconnect
-		// Generic Oauth2 API is an exception because it needs to save the scope
-
-		if (
-			decryptedDataOriginal?.scope &&
-			credential.type.includes('OAuth2') &&
-			!GENERIC_OAUTH2_CREDENTIALS_WITH_EDITABLE_SCOPE.includes(credential.type)
-		) {
-			delete decryptedDataOriginal.scope;
-		}
-
-		const oauthCredentials = await this.applyDefaultsAndOverwrites<OAuth2CredentialData>(
-			credential,
-			decryptedDataOriginal,
-			additionalData,
-		);
+		const credential = await this.oauthService.getCredential(req);
+		const oauthCredentials: OAuth2CredentialData =
+			await this.oauthService.getOAuthCredentials<OAuth2CredentialData>(credential);
 
 		const toUpdate: ICredentialDataDecryptedObject = {};
 
@@ -102,7 +89,7 @@ export class OAuth2CredentialController extends AbstractOAuthController {
 				authentication,
 			);
 			const registerPayload = {
-				redirect_uris: [`${this.baseUrl}/callback`],
+				redirect_uris: [`${this.oauthService.getBaseUrl(OauthVersion.V2)}/callback`],
 				token_endpoint_auth_method,
 				grant_types,
 				response_types: ['code'],
@@ -135,10 +122,10 @@ export class OAuth2CredentialController extends AbstractOAuthController {
 		}
 
 		// Generate a CSRF prevention token and send it as an OAuth2 state string
-		const [csrfSecret, state] = this.createCsrfState(
-			credential.id,
-			skipAuthOnOAuthCallback ? undefined : req.user.id,
-		);
+		const [csrfSecret, state] = this.oauthService.createCsrfState({
+			cid: credential.id,
+			userId: skipAuthOnOAuthCallback ? undefined : req.user.id,
+		});
 
 		const oAuthOptions = {
 			...this.convertCredentialToOptions(oauthCredentials),
@@ -162,7 +149,7 @@ export class OAuth2CredentialController extends AbstractOAuthController {
 			toUpdate.codeVerifier = code_verifier;
 		}
 
-		await this.encryptAndSaveData(credential, toUpdate);
+		await this.oauthService.encryptAndSaveData(credential, toUpdate);
 
 		const oAuthObj = new ClientOAuth2(oAuthOptions);
 		const returnUri = oAuthObj.code.getUri();
@@ -181,7 +168,7 @@ export class OAuth2CredentialController extends AbstractOAuthController {
 		try {
 			const { code, state: encodedState } = req.query;
 			if (!code || !encodedState) {
-				return this.renderCallbackError(
+				return this.oauthService.renderCallbackError(
 					res,
 					'Insufficient parameters for OAuth2 callback.',
 					`Received following query parameters: ${JSON.stringify(req.query)}`,
@@ -189,7 +176,7 @@ export class OAuth2CredentialController extends AbstractOAuthController {
 			}
 
 			const [credential, decryptedDataOriginal, oauthCredentials] =
-				await this.resolveCredential<OAuth2CredentialData>(req);
+				await this.oauthService.resolveCredential<OAuth2CredentialData>(req);
 
 			let options: Partial<ClientOAuth2Options> = {};
 
@@ -233,7 +220,7 @@ export class OAuth2CredentialController extends AbstractOAuthController {
 				...oauthToken.data,
 			};
 
-			await this.encryptAndSaveData(credential, { oauthTokenData }, ['csrfSecret']);
+			await this.oauthService.encryptAndSaveData(credential, { oauthTokenData }, ['csrfSecret']);
 
 			this.logger.debug('OAuth2 callback successful for credential', {
 				credentialId: credential.id,
@@ -242,7 +229,7 @@ export class OAuth2CredentialController extends AbstractOAuthController {
 			return res.render('oauth-callback');
 		} catch (e) {
 			const error = ensureError(e);
-			return this.renderCallbackError(
+			return this.oauthService.renderCallbackError(
 				res,
 				error.message,
 				'body' in error ? jsonStringify(error.body) : undefined,
@@ -257,7 +244,7 @@ export class OAuth2CredentialController extends AbstractOAuthController {
 			accessTokenUri: credential.accessTokenUrl ?? '',
 			authorizationUri: credential.authUrl ?? '',
 			authentication: credential.authentication ?? 'header',
-			redirectUri: `${this.baseUrl}/callback`,
+			redirectUri: `${this.oauthService.getBaseUrl(OauthVersion.V2)}/callback`,
 			scopes: split(credential.scope ?? 'openid', ','),
 			scopesSeparator: credential.scope?.includes(',') ? ',' : ' ',
 			ignoreSSLIssues: credential.ignoreSSLIssues ?? false,

packages/cli/src/controllers/owner.controller.ts

@@ -1,82 +1,31 @@
 import { DismissBannerRequestDto, OwnerSetupRequestDto } from '@n8n/api-types';
-import { Logger } from '@n8n/backend-common';
-import {
-	AuthenticatedRequest,
-	GLOBAL_OWNER_ROLE,
-	SettingsRepository,
-	UserRepository,
-} from '@n8n/db';
+import { AuthenticatedRequest } from '@n8n/db';
 import { Body, GlobalScope, Post, RestController } from '@n8n/decorators';
 import { Response } from 'express';
 
 import { AuthService } from '@/auth/auth.service';
-import config from '@/config';
-import { BadRequestError } from '@/errors/response-errors/bad-request.error';
-import { EventService } from '@/events/event.service';
-import { validateEntity } from '@/generic-helpers';
 import { PostHogClient } from '@/posthog';
 import { BannerService } from '@/services/banner.service';
-import { PasswordUtility } from '@/services/password.utility';
 import { UserService } from '@/services/user.service';
+import { OwnershipService } from '@/services/ownership.service';
 
 @RestController('/owner')
 export class OwnerController {
 	constructor(
-		private readonly logger: Logger,
-		private readonly eventService: EventService,
-		private readonly settingsRepository: SettingsRepository,
 		private readonly authService: AuthService,
 		private readonly bannerService: BannerService,
 		private readonly userService: UserService,
-		private readonly passwordUtility: PasswordUtility,
 		private readonly postHog: PostHogClient,
-		private readonly userRepository: UserRepository,
+		private readonly ownershipService: OwnershipService,
 	) {}
 
 	/**
-	 * Promote a shell into the owner of the n8n instance,
-	 * and enable `isInstanceOwnerSetUp` setting.
+	 * Promote a shell into the owner of the n8n instance
 	 */
 	@Post('/setup', { skipAuth: true })
 	async setupOwner(req: AuthenticatedRequest, res: Response, @Body payload: OwnerSetupRequestDto) {
-		const { email, firstName, lastName, password } = payload;
-
-		if (config.getEnv('userManagement.isInstanceOwnerSetUp')) {
-			this.logger.debug(
-				'Request to claim instance ownership failed because instance owner already exists',
-			);
-			throw new BadRequestError('Instance owner already setup');
-		}
-
-		let owner = await this.userRepository.findOneOrFail({
-			where: { role: { slug: GLOBAL_OWNER_ROLE.slug } },
-			relations: ['role'],
-		});
-		owner.email = email;
-		owner.firstName = firstName;
-		owner.lastName = lastName;
-		owner.password = await this.passwordUtility.hash(password);
-
-		// TODO: move XSS validation out into the DTO class
-		await validateEntity(owner);
-
-		owner = await this.userRepository.save(owner, { transaction: false });
-
-		this.logger.info('Owner was set up successfully');
-
-		await this.settingsRepository.update(
-			{ key: 'userManagement.isInstanceOwnerSetUp' },
-			{ value: JSON.stringify(true) },
-		);
-
-		config.set('userManagement.isInstanceOwnerSetUp', true);
-
-		this.logger.debug('Setting isInstanceOwnerSetUp updated successfully');
-
+		const owner = await this.ownershipService.setupOwner(payload);
 		this.authService.issueCookie(res, owner, req.authInfo?.usedMfa ?? false, req.browserId);
-
-		this.eventService.emit('instance-owner-setup', { userId: owner.id });
-
 		return await this.userService.toPublic(owner, { posthog: this.postHog, withScopes: true });
 	}
 

packages/cli/src/credentials/__tests__/credentials.controller.test.ts

@@ -1,14 +1,15 @@
+import type { LicenseState } from '@n8n/backend-common';
 import type { AuthenticatedRequest, SharedCredentialsRepository, CredentialsEntity } from '@n8n/db';
 import { GLOBAL_OWNER_ROLE, GLOBAL_MEMBER_ROLE } from '@n8n/db';
 import { mock } from 'jest-mock-extended';
 
-import { createRawProjectData } from '@/__tests__/project.test-data';
-import type { EventService } from '@/events/event.service';
-
 import { createdCredentialsWithScopes, createNewCredentialsPayload } from './credentials.test-data';
+import type { CredentialsFinderService } from '../credentials-finder.service';
 import { CredentialsController } from '../credentials.controller';
 import type { CredentialsService } from '../credentials.service';
-import type { CredentialsFinderService } from '../credentials-finder.service';
+
+import { createRawProjectData } from '@/__tests__/project.test-data';
+import type { EventService } from '@/events/event.service';
 import type { CredentialRequest } from '@/requests';
 
 describe('CredentialsController', () => {
@@ -16,13 +17,14 @@ describe('CredentialsController', () => {
 	const credentialsService = mock<CredentialsService>();
 	const sharedCredentialsRepository = mock<SharedCredentialsRepository>();
 	const credentialsFinderService = mock<CredentialsFinderService>();
+	const licenseState = mock<LicenseState>();
 
 	const credentialsController = new CredentialsController(
 		mock(),
 		credentialsService,
 		mock(),
 		mock(),
-		mock(),
+		licenseState,
 		mock(),
 		mock(),
 		sharedCredentialsRepository,
@@ -126,7 +128,7 @@ describe('CredentialsController', () => {
 			] as any);
 		});
 
-		it('should allow owner to set isGlobal to true', async () => {
+		it('should not allow owner to set isGlobal to true if not licensed', async () => {
 			// ARRANGE
 			const ownerReq = {
 				user: { id: 'owner-id', role: GLOBAL_OWNER_ROLE },
@@ -139,6 +141,34 @@ describe('CredentialsController', () => {
 				},
 			} as unknown as CredentialRequest.Update;
 
+			licenseState.isSharingLicensed.mockReturnValue(false);
+
+			credentialsFinderService.findCredentialForUser.mockResolvedValue(existingCredential);
+
+			// ACT
+			await expect(credentialsController.updateCredentials(ownerReq)).rejects.toThrowError(
+				'You are not licensed for sharing credentials',
+			);
+
+			// ASSERT
+			expect(credentialsService.update).not.toHaveBeenCalled();
+		});
+
+		it('should allow owner to set isGlobal to true if licensed', async () => {
+			// ARRANGE
+			const ownerReq = {
+				user: { id: 'owner-id', role: GLOBAL_OWNER_ROLE },
+				params: { credentialId },
+				body: {
+					name: 'Updated Credential',
+					type: 'apiKey',
+					data: { apiKey: 'updated-key' },
+					isGlobal: true,
+				},
+			} as unknown as CredentialRequest.Update;
+
+			licenseState.isSharingLicensed.mockReturnValue(true);
+
 			credentialsFinderService.findCredentialForUser.mockResolvedValue(existingCredential);
 			credentialsService.update.mockResolvedValue({
 				...existingCredential,
@@ -163,7 +193,7 @@ describe('CredentialsController', () => {
 			});
 		});
 
-		it('should allow owner to set isGlobal to false', async () => {
+		it('should allow owner to set isGlobal to false if licensed', async () => {
 			// ARRANGE
 			const globalCredential = mock<CredentialsEntity>({
 				...existingCredential,
@@ -180,6 +210,8 @@ describe('CredentialsController', () => {
 				},
 			} as unknown as CredentialRequest.Update;
 
+			licenseState.isSharingLicensed.mockReturnValue(true);
+
 			credentialsFinderService.findCredentialForUser.mockResolvedValue(globalCredential);
 			credentialsService.update.mockResolvedValue({
 				...globalCredential,
@@ -198,7 +230,7 @@ describe('CredentialsController', () => {
 			);
 		});
 
-		it('should prevent non-owner from changing isGlobal', async () => {
+		it('should prevent non-owner from changing isGlobal if licensed', async () => {
 			// ARRANGE
 			const memberReq = {
 				user: { id: 'member-id', role: GLOBAL_MEMBER_ROLE },
@@ -211,6 +243,8 @@ describe('CredentialsController', () => {
 				},
 			} as unknown as CredentialRequest.Update;
 
+			licenseState.isSharingLicensed.mockReturnValue(true);
+
 			credentialsFinderService.findCredentialForUser.mockResolvedValue(existingCredential);
 
 			// ACT
@@ -235,6 +269,8 @@ describe('CredentialsController', () => {
 				},
 			} as unknown as CredentialRequest.Update;
 
+			licenseState.isSharingLicensed.mockReturnValue(true);
+
 			credentialsFinderService.findCredentialForUser.mockResolvedValue({
 				...existingCredential,
 				isGlobal: true,

packages/cli/src/credentials/credentials.controller.ts

@@ -4,7 +4,7 @@ import {
 	CredentialsGetOneRequestQuery,
 	GenerateCredentialNameRequestQuery,
 } from '@n8n/api-types';
-import { Logger } from '@n8n/backend-common';
+import { LicenseState, Logger } from '@n8n/backend-common';
 import { GlobalConfig } from '@n8n/config';
 import {
 	SharedCredentials,
@@ -40,7 +40,6 @@ import { BadRequestError } from '@/errors/response-errors/bad-request.error';
 import { ForbiddenError } from '@/errors/response-errors/forbidden.error';
 import { NotFoundError } from '@/errors/response-errors/not-found.error';
 import { EventService } from '@/events/event.service';
-import { License } from '@/license';
 import { listQueryMiddleware } from '@/middlewares';
 import { CredentialRequest } from '@/requests';
 import { NamingService } from '@/services/naming.service';
@@ -54,7 +53,7 @@ export class CredentialsController {
 		private readonly credentialsService: CredentialsService,
 		private readonly enterpriseCredentialsService: EnterpriseCredentialsService,
 		private readonly namingService: NamingService,
-		private readonly license: License,
+		private readonly licenseState: LicenseState,
 		private readonly logger: Logger,
 		private readonly userManagementMailer: UserManagementMailer,
 		private readonly sharedCredentialsRepository: SharedCredentialsRepository,
@@ -114,7 +113,7 @@ export class CredentialsController {
 		@Param('credentialId') credentialId: string,
 		@Query query: CredentialsGetOneRequestQuery,
 	) {
-		const { shared, ...credential } = this.license.isSharingEnabled()
+		const { shared, ...credential } = this.licenseState.isSharingLicensed()
 			? await this.enterpriseCredentialsService.getOne(
 					req.user,
 					credentialId,
@@ -246,6 +245,10 @@ export class CredentialsController {
 		// Update isGlobal if provided in the payload and user has permission
 		const isGlobal = body.isGlobal;
 		if (isGlobal !== undefined && isGlobal !== credential.isGlobal) {
+			if (!this.licenseState.isSharingLicensed()) {
+				throw new ForbiddenError('You are not licensed for sharing credentials');
+			}
+
 			const canShareGlobally = hasGlobalScope(req.user, 'credential:shareGlobally');
 			if (!canShareGlobally) {
 				throw new ForbiddenError(

packages/cli/src/modules/breaking-changes/rules/v2/__tests__/settings-file-permissions.rule.test.ts

@@ -1,16 +1,20 @@
-import type { InstanceSettingsConfig } from '@n8n/config';
+import type { GlobalConfig } from '@n8n/config';
 import { mock } from 'jest-mock-extended';
 
 import { SettingsFilePermissionsRule } from '../settings-file-permissions.rule';
 
 describe('SettingsFilePermissionsRule', () => {
 	let rule: SettingsFilePermissionsRule;
-	const instanceSettingsConfig = mock<InstanceSettingsConfig>({});
+	const mockGlobalConfig = mock<GlobalConfig>({
+		deployment: { type: 'default' },
+	});
 	let originalEnvValue: string | undefined;
 
 	beforeEach(() => {
-		rule = new SettingsFilePermissionsRule(instanceSettingsConfig);
+		rule = new SettingsFilePermissionsRule(mockGlobalConfig);
 		originalEnvValue = process.env.N8N_ENFORCE_SETTINGS_FILE_PERMISSIONS;
+		// Clear env var before each test
+		delete process.env.N8N_ENFORCE_SETTINGS_FILE_PERMISSIONS;
 	});
 
 	afterEach(() => {
@@ -22,8 +26,21 @@ describe('SettingsFilePermissionsRule', () => {
 	});
 
 	describe('detect()', () => {
-		it('should not be affected when enforceSettingsFilePermissions is set to false', async () => {
-			instanceSettingsConfig.enforceSettingsFilePermissions = false;
+		it('should not be affected on cloud deployments', async () => {
+			const cloudGlobalConfig = mock<GlobalConfig>({
+				deployment: { type: 'cloud' },
+			});
+			const cloudRule = new SettingsFilePermissionsRule(cloudGlobalConfig);
+
+			const result = await cloudRule.detect();
+
+			expect(result.isAffected).toBe(false);
+			expect(result.instanceIssues).toHaveLength(0);
+			expect(result.recommendations).toHaveLength(0);
+		});
+
+		it('should not be affected when N8N_ENFORCE_SETTINGS_FILE_PERMISSIONS is explicitly set to false', async () => {
+			process.env.N8N_ENFORCE_SETTINGS_FILE_PERMISSIONS = 'false';
 
 			const result = await rule.detect();
 
@@ -32,8 +49,18 @@ describe('SettingsFilePermissionsRule', () => {
 			expect(result.recommendations).toHaveLength(0);
 		});
 
-		it('should be affected when enforceSettingsFilePermissions is not set to false', async () => {
-			instanceSettingsConfig.enforceSettingsFilePermissions = true;
+		it('should not be affected when N8N_ENFORCE_SETTINGS_FILE_PERMISSIONS is explicitly set to true', async () => {
+			process.env.N8N_ENFORCE_SETTINGS_FILE_PERMISSIONS = 'true';
+
+			const result = await rule.detect();
+
+			expect(result.isAffected).toBe(false);
+			expect(result.instanceIssues).toHaveLength(0);
+			expect(result.recommendations).toHaveLength(0);
+		});
+
+		it('should be affected when N8N_ENFORCE_SETTINGS_FILE_PERMISSIONS is not set (default behavior change)', async () => {
+			// Env var is not set (cleared in beforeEach)
 			const result = await rule.detect();
 
 			expect(result.isAffected).toBe(true);

packages/cli/src/modules/breaking-changes/rules/v2/__tests__/task-runner-docker-image.rule.test.ts

@@ -1,10 +1,16 @@
+import type { GlobalConfig } from '@n8n/config';
+import { mock } from 'jest-mock-extended';
+
 import { TaskRunnerDockerImageRule } from '../task-runner-docker-image.rule';
 
 describe('TaskRunnerDockerImageRule', () => {
 	let rule: TaskRunnerDockerImageRule;
 
 	beforeEach(() => {
-		rule = new TaskRunnerDockerImageRule();
+		const mockGlobalConfig = mock<GlobalConfig>({
+			deployment: { type: 'default' },
+		});
+		rule = new TaskRunnerDockerImageRule(mockGlobalConfig);
 	});
 
 	describe('getMetadata()', () => {
@@ -18,6 +24,19 @@ describe('TaskRunnerDockerImageRule', () => {
 	});
 
 	describe('detect()', () => {
+		it('should not be affected on cloud deployments', async () => {
+			const mockGlobalConfig = mock<GlobalConfig>({
+				deployment: { type: 'cloud' },
+			});
+			const cloudRule = new TaskRunnerDockerImageRule(mockGlobalConfig);
+
+			const result = await cloudRule.detect();
+
+			expect(result.isAffected).toBe(false);
+			expect(result.instanceIssues).toHaveLength(0);
+			expect(result.recommendations).toHaveLength(0);
+		});
+
 		it('should always be affected (informational)', async () => {
 			const result = await rule.detect();
 

packages/cli/src/modules/breaking-changes/rules/v2/__tests__/task-runners.rule.test.ts

@@ -1,12 +1,35 @@
-import type { TaskRunnersConfig } from '@n8n/config';
+import type { GlobalConfig, TaskRunnersConfig } from '@n8n/config';
+import { mock } from 'jest-mock-extended';
 
 import { TaskRunnersRule } from '../task-runners.rule';
 
 describe('TaskRunnersRule', () => {
+	let mockGlobalConfig: GlobalConfig;
+
+	beforeEach(() => {
+		mockGlobalConfig = mock<GlobalConfig>({
+			deployment: { type: 'default' },
+		});
+	});
+
 	describe('detect()', () => {
+		it('should not be affected on cloud deployments', async () => {
+			const mockConfig = { enabled: false } as TaskRunnersConfig;
+			const cloudGlobalConfig = mock<GlobalConfig>({
+				deployment: { type: 'cloud' },
+			});
+			const rule = new TaskRunnersRule(mockConfig, cloudGlobalConfig);
+
+			const result = await rule.detect();
+
+			expect(result.isAffected).toBe(false);
+			expect(result.instanceIssues).toHaveLength(0);
+			expect(result.recommendations).toHaveLength(0);
+		});
+
 		it('should not be affected when runners are already enabled', async () => {
 			const mockConfig = { enabled: true } as TaskRunnersConfig;
-			const rule = new TaskRunnersRule(mockConfig);
+			const rule = new TaskRunnersRule(mockConfig, mockGlobalConfig);
 
 			const result = await rule.detect();
 
@@ -16,18 +39,19 @@ describe('TaskRunnersRule', () => {
 
 		it('should be affected when runners are not enabled', async () => {
 			const mockConfig = { enabled: false } as TaskRunnersConfig;
-			const rule = new TaskRunnersRule(mockConfig);
+			const rule = new TaskRunnersRule(mockConfig, mockGlobalConfig);
 
 			const result = await rule.detect();
 
 			expect(result.isAffected).toBe(true);
 			expect(result.instanceIssues).toHaveLength(1);
 			expect(result.instanceIssues[0].title).toBe('Task Runners will be enabled by default');
+			expect(result.recommendations).toHaveLength(3);
 		});
 
 		it('should be affected when runners are explicitly disabled', async () => {
 			const mockConfig = { enabled: false } as TaskRunnersConfig;
-			const rule = new TaskRunnersRule(mockConfig);
+			const rule = new TaskRunnersRule(mockConfig, mockGlobalConfig);
 
 			const result = await rule.detect();
 

packages/cli/src/modules/breaking-changes/rules/v2/settings-file-permissions.rule.ts

@@ -1,4 +1,4 @@
-import { InstanceSettingsConfig } from '@n8n/config';
+import { GlobalConfig } from '@n8n/config';
 import { Service } from '@n8n/di';
 
 import type {
@@ -10,7 +10,7 @@ import { BreakingChangeCategory } from '../../types';
 
 @Service()
 export class SettingsFilePermissionsRule implements IBreakingChangeInstanceRule {
-	constructor(private readonly instanceSettingsConfig: InstanceSettingsConfig) {}
+	constructor(private readonly globalConfig: GlobalConfig) {}
 
 	id: string = 'settings-file-permissions-v2';
 
@@ -28,9 +28,18 @@ export class SettingsFilePermissionsRule implements IBreakingChangeInstanceRule
 	}
 
 	async detect(): Promise<InstanceDetectionReport> {
-		// If enforceSettingsFilePermissions is explicitly set to 'false', users are not affected
-		// because they've configured the system to not enforce file permissions
-		if (!this.instanceSettingsConfig.enforceSettingsFilePermissions) {
+		// Not relevant for cloud deployments - cloud manages infrastructure and file permissions
+		if (this.globalConfig.deployment.type === 'cloud') {
+			return {
+				isAffected: false,
+				instanceIssues: [],
+				recommendations: [],
+			};
+		}
+
+		// If N8N_ENFORCE_SETTINGS_FILE_PERMISSIONS is explicitly set to any value, users are not affected
+		// because they've already handled the configuration and are aware of this setting.
+		if (process.env.N8N_ENFORCE_SETTINGS_FILE_PERMISSIONS) {
 			return {
 				isAffected: false,
 				instanceIssues: [],

packages/cli/src/modules/breaking-changes/rules/v2/task-runner-docker-image.rule.ts

@@ -1,3 +1,4 @@
+import { GlobalConfig } from '@n8n/config';
 import { Service } from '@n8n/di';
 
 import type {
@@ -9,6 +10,8 @@ import { BreakingChangeCategory } from '../../types';
 
 @Service()
 export class TaskRunnerDockerImageRule implements IBreakingChangeInstanceRule {
+	constructor(private readonly globalConfig: GlobalConfig) {}
+
 	id: string = 'task-runner-docker-image-v2';
 
 	getMetadata(): BreakingChangeRuleMetadata {
@@ -25,6 +28,15 @@ export class TaskRunnerDockerImageRule implements IBreakingChangeInstanceRule {
 	}
 
 	async detect(): Promise<InstanceDetectionReport> {
+		// Not relevant for cloud deployments - cloud manages Docker images
+		if (this.globalConfig.deployment.type === 'cloud') {
+			return {
+				isAffected: false,
+				instanceIssues: [],
+				recommendations: [],
+			};
+		}
+
 		const result: InstanceDetectionReport = {
 			isAffected: true,
 			instanceIssues: [

packages/cli/src/modules/breaking-changes/rules/v2/task-runners.rule.ts

@@ -1,4 +1,4 @@
-import { TaskRunnersConfig } from '@n8n/config';
+import { GlobalConfig, TaskRunnersConfig } from '@n8n/config';
 import { Service } from '@n8n/di';
 
 import type {
@@ -10,7 +10,10 @@ import { BreakingChangeCategory } from '../../types';
 
 @Service()
 export class TaskRunnersRule implements IBreakingChangeInstanceRule {
-	constructor(private readonly taskRunnersConfig: TaskRunnersConfig) {}
+	constructor(
+		private readonly taskRunnersConfig: TaskRunnersConfig,
+		private readonly globalConfig: GlobalConfig,
+	) {}
 
 	id: string = 'task-runners-v2';
 
@@ -27,6 +30,15 @@ export class TaskRunnersRule implements IBreakingChangeInstanceRule {
 	}
 
 	async detect(): Promise<InstanceDetectionReport> {
+		// Not relevant for cloud deployments - cloud manages task runner infrastructure
+		if (this.globalConfig.deployment.type === 'cloud') {
+			return {
+				isAffected: false,
+				instanceIssues: [],
+				recommendations: [],
+			};
+		}
+
 		const result: InstanceDetectionReport = {
 			isAffected: false,
 			instanceIssues: [],

packages/cli/src/modules/chat-hub/chat-hub.controller.ts

@@ -38,11 +38,13 @@ import { ChatHubAgentService } from './chat-hub-agent.service';
 import { ChatHubAttachmentService } from './chat-hub.attachment.service';
 import { ChatHubService } from './chat-hub.service';
 import { ChatModelsRequestDto } from './dto/chat-models-request.dto';
+import { ChatHubModelsService } from './chat-hub.models.service';
 
 @RestController('/chat')
 export class ChatHubController {
 	constructor(
 		private readonly chatService: ChatHubService,
+		private readonly chatModelsService: ChatHubModelsService,
 		private readonly chatAgentService: ChatHubAgentService,
 		private readonly chatAttachmentService: ChatHubAttachmentService,
 		private readonly logger: Logger,
@@ -55,7 +57,7 @@ export class ChatHubController {
 		_res: Response,
 		@Body payload: ChatModelsRequestDto,
 	): Promise<ChatModelsResponse> {
-		return await this.chatService.getModels(req.user, payload.credentials);
+		return await this.chatModelsService.getModels(req.user, payload.credentials);
 	}
 
 	@Get('/conversations')

packages/cli/src/modules/chat-hub/chat-hub.models.service.ts

@@ -0,0 +1,811 @@
+import { In, WorkflowRepository, type User } from '@n8n/db';
+import { getBase } from '@/workflow-execute-additional-data';
+
+import { ChatHubAgentService } from './chat-hub-agent.service';
+import { ChatHubWorkflowService } from './chat-hub-workflow.service';
+
+import { CredentialsFinderService } from '@/credentials/credentials-finder.service';
+import { DynamicNodeParametersService } from '@/services/dynamic-node-parameters.service';
+import { WorkflowService } from '@/workflows/workflow.service';
+import { getModelMetadata, PROVIDER_NODE_TYPE_MAP } from './chat-hub.constants';
+import {
+	AGENT_LANGCHAIN_NODE_TYPE,
+	CHAT_TRIGGER_NODE_TYPE,
+	type INodeCredentials,
+	type INodePropertyOptions,
+	type IWorkflowExecuteAdditionalData,
+} from 'n8n-workflow';
+import {
+	chatHubProviderSchema,
+	emptyChatModelsResponse,
+	PROVIDER_CREDENTIAL_TYPE_MAP,
+	type ChatHubLLMProvider,
+	type ChatHubProvider,
+	type ChatModelDto,
+	type ChatModelsResponse,
+} from '@n8n/api-types';
+import { validChatTriggerParamsShape } from './chat-hub.types';
+import { Service } from '@n8n/di';
+
+@Service()
+export class ChatHubModelsService {
+	constructor(
+		private readonly nodeParametersService: DynamicNodeParametersService,
+		private readonly workflowService: WorkflowService,
+		private readonly workflowRepository: WorkflowRepository,
+		private readonly credentialsFinderService: CredentialsFinderService,
+		private readonly chatHubAgentService: ChatHubAgentService,
+		private readonly chatHubWorkflowService: ChatHubWorkflowService,
+	) {}
+
+	async getModels(
+		user: User,
+		credentialIds: Record<ChatHubLLMProvider, string | null>,
+	): Promise<ChatModelsResponse> {
+		const additionalData = await getBase({ userId: user.id });
+		const providers = chatHubProviderSchema.options;
+
+		const allCredentials = await this.credentialsFinderService.findCredentialsForUser(user, [
+			'credential:read',
+		]);
+
+		const responses = await Promise.all(
+			providers.map<Promise<[ChatHubProvider, ChatModelsResponse[ChatHubProvider]]>>(
+				async (provider: ChatHubProvider) => {
+					const credentials: INodeCredentials = {};
+
+					if (provider !== 'n8n' && provider !== 'custom-agent') {
+						const credentialId = credentialIds[provider];
+						if (!credentialId) {
+							return [provider, { models: [] }];
+						}
+
+						// Ensure the user has the permission to read the credential
+						if (!allCredentials.some((credential) => credential.id === credentialId)) {
+							return [
+								provider,
+								{ models: [], error: 'Could not retrieve models. Verify credentials.' },
+							];
+						}
+
+						credentials[PROVIDER_CREDENTIAL_TYPE_MAP[provider]] = { name: '', id: credentialId };
+					}
+
+					try {
+						return [
+							provider,
+							await this.fetchModelsForProvider(user, provider, credentials, additionalData),
+						];
+					} catch {
+						return [
+							provider,
+							{ models: [], error: 'Could not retrieve models. Verify credentials.' },
+						];
+					}
+				},
+			),
+		);
+
+		return responses.reduce<ChatModelsResponse>(
+			(acc, [provider, res]) => {
+				acc[provider] = res;
+				return acc;
+			},
+			{ ...emptyChatModelsResponse },
+		);
+	}
+
+	private async fetchModelsForProvider(
+		user: User,
+		provider: ChatHubProvider,
+		credentials: INodeCredentials,
+		additionalData: IWorkflowExecuteAdditionalData,
+	): Promise<ChatModelsResponse[ChatHubProvider]> {
+		switch (provider) {
+			case 'openai': {
+				const rawModels = await this.fetchOpenAiModels(credentials, additionalData);
+				return { models: this.transformAndFilterModels(rawModels, 'openai') };
+			}
+			case 'anthropic': {
+				const rawModels = await this.fetchAnthropicModels(credentials, additionalData);
+				return { models: this.transformAndFilterModels(rawModels, 'anthropic') };
+			}
+			case 'google': {
+				const rawModels = await this.fetchGoogleModels(credentials, additionalData);
+				return { models: this.transformAndFilterModels(rawModels, 'google') };
+			}
+			case 'ollama': {
+				const rawModels = await this.fetchOllamaModels(credentials, additionalData);
+				return { models: this.transformAndFilterModels(rawModels, 'ollama') };
+			}
+			case 'azureOpenAi': {
+				const rawModels = this.fetchAzureOpenAiModels(credentials, additionalData);
+				return { models: this.transformAndFilterModels(rawModels, 'azureOpenAi') };
+			}
+			case 'azureEntraId': {
+				const rawModels = this.fetchAzureEntraIdModels(credentials, additionalData);
+				return { models: this.transformAndFilterModels(rawModels, 'azureEntraId') };
+			}
+			case 'awsBedrock': {
+				const rawModels = await this.fetchAwsBedrockModels(credentials, additionalData);
+				return { models: this.transformAndFilterModels(rawModels, 'awsBedrock') };
+			}
+			case 'vercelAiGateway': {
+				const rawModels = await this.fetchVercelAiGatewayModels(credentials, additionalData);
+				return { models: this.transformAndFilterModels(rawModels, 'vercelAiGateway') };
+			}
+			case 'xAiGrok': {
+				const rawModels = await this.fetchXAiGrokModels(credentials, additionalData);
+				return { models: this.transformAndFilterModels(rawModels, 'xAiGrok') };
+			}
+			case 'groq': {
+				const rawModels = await this.fetchGroqModels(credentials, additionalData);
+				return { models: this.transformAndFilterModels(rawModels, 'groq') };
+			}
+			case 'openRouter': {
+				const rawModels = await this.fetchOpenRouterModels(credentials, additionalData);
+				return { models: this.transformAndFilterModels(rawModels, 'openRouter') };
+			}
+			case 'deepSeek': {
+				const rawModels = await this.fetchDeepSeekModels(credentials, additionalData);
+				return { models: this.transformAndFilterModels(rawModels, 'deepSeek') };
+			}
+			case 'cohere': {
+				const rawModels = await this.fetchCohereModels(credentials, additionalData);
+				return { models: this.transformAndFilterModels(rawModels, 'cohere') };
+			}
+			case 'mistralCloud': {
+				const rawModels = await this.fetchMistralCloudModels(credentials, additionalData);
+				return { models: this.transformAndFilterModels(rawModels, 'mistralCloud') };
+			}
+			case 'n8n':
+				return await this.fetchAgentWorkflowsAsModels(user);
+			case 'custom-agent':
+				return await this.chatHubAgentService.getAgentsByUserIdAsModels(user.id);
+		}
+	}
+
+	private async fetchOpenAiModels(
+		credentials: INodeCredentials,
+		additionalData: IWorkflowExecuteAdditionalData,
+	): Promise<INodePropertyOptions[]> {
+		const resourceLocatorResults = await this.nodeParametersService.getResourceLocatorResults(
+			'searchModels',
+			'parameters.model',
+			additionalData,
+			PROVIDER_NODE_TYPE_MAP.openai,
+			{},
+			credentials,
+		);
+
+		return resourceLocatorResults.results;
+	}
+
+	private async fetchAnthropicModels(
+		credentials: INodeCredentials,
+		additionalData: IWorkflowExecuteAdditionalData,
+	): Promise<INodePropertyOptions[]> {
+		const resourceLocatorResults = await this.nodeParametersService.getResourceLocatorResults(
+			'searchModels',
+			'parameters.model',
+			additionalData,
+			PROVIDER_NODE_TYPE_MAP.anthropic,
+			{},
+			credentials,
+		);
+
+		return resourceLocatorResults.results;
+	}
+
+	private async fetchGoogleModels(
+		credentials: INodeCredentials,
+		additionalData: IWorkflowExecuteAdditionalData,
+	): Promise<INodePropertyOptions[]> {
+		return await this.nodeParametersService.getOptionsViaLoadOptions(
+			{
+				// From Gemini node
+				// https://github.com/n8n-io/n8n/blob/master/packages/%40n8n/nodes-langchain/nodes/llms/LmChatGoogleGemini/LmChatGoogleGemini.node.ts#L75
+				routing: {
+					request: {
+						method: 'GET',
+						url: '/v1beta/models',
+					},
+					output: {
+						postReceive: [
+							{
+								type: 'rootProperty',
+								properties: {
+									property: 'models',
+								},
+							},
+							{
+								type: 'filter',
+								properties: {
+									pass: "={{ !$responseItem.name.includes('embedding') }}",
+								},
+							},
+							{
+								type: 'setKeyValue',
+								properties: {
+									name: '={{$responseItem.name}}',
+									value: '={{$responseItem.name}}',
+									description: '={{$responseItem.description}}',
+								},
+							},
+							{
+								type: 'sort',
+								properties: {
+									key: 'name',
+								},
+							},
+						],
+					},
+				},
+			},
+			additionalData,
+			PROVIDER_NODE_TYPE_MAP.google,
+			{},
+			credentials,
+		);
+	}
+
+	private async fetchOllamaModels(
+		credentials: INodeCredentials,
+		additionalData: IWorkflowExecuteAdditionalData,
+	): Promise<INodePropertyOptions[]> {
+		return await this.nodeParametersService.getOptionsViaLoadOptions(
+			{
+				// From Ollama Model node
+				// https://github.com/n8n-io/n8n/blob/master/packages/%40n8n/nodes-langchain/nodes/llms/LMOllama/description.ts#L24
+				routing: {
+					request: {
+						method: 'GET',
+						url: '/api/tags',
+					},
+					output: {
+						postReceive: [
+							{
+								type: 'rootProperty',
+								properties: {
+									property: 'models',
+								},
+							},
+							{
+								type: 'setKeyValue',
+								properties: {
+									name: '={{$responseItem.name}}',
+									value: '={{$responseItem.name}}',
+								},
+							},
+							{
+								type: 'sort',
+								properties: {
+									key: 'name',
+								},
+							},
+						],
+					},
+				},
+			},
+			additionalData,
+			PROVIDER_NODE_TYPE_MAP.ollama,
+			{},
+			credentials,
+		);
+	}
+
+	private fetchAzureOpenAiModels(
+		_credentials: INodeCredentials,
+		_additionalData: IWorkflowExecuteAdditionalData,
+	): INodePropertyOptions[] {
+		// Azure doesn't appear to offer a way to list available models via API.
+		// If we add support for this in the future on the Azure OpenAI node we should copy that
+		// implementation here too.
+		return [];
+	}
+
+	private fetchAzureEntraIdModels(
+		_credentials: INodeCredentials,
+		_additionalData: IWorkflowExecuteAdditionalData,
+	): INodePropertyOptions[] {
+		return [];
+	}
+
+	private async fetchAwsBedrockModels(
+		credentials: INodeCredentials,
+		additionalData: IWorkflowExecuteAdditionalData,
+	): Promise<INodePropertyOptions[]> {
+		// From AWS Bedrock node
+		// https://github.com/n8n-io/n8n/blob/master/packages/%40n8n/nodes-langchain/nodes/llms/LmChatAwsBedrock/LmChatAwsBedrock.node.ts#L100
+		// https://github.com/n8n-io/n8n/blob/master/packages/%40n8n/nodes-langchain/nodes/llms/LmChatAwsBedrock/LmChatAwsBedrock.node.ts#L155
+		const foundationModelsRequest = this.nodeParametersService.getOptionsViaLoadOptions(
+			{
+				routing: {
+					request: {
+						method: 'GET',
+						url: '/foundation-models?&byOutputModality=TEXT&byInferenceType=ON_DEMAND',
+					},
+					output: {
+						postReceive: [
+							{
+								type: 'rootProperty',
+								properties: {
+									property: 'modelSummaries',
+								},
+							},
+							{
+								type: 'setKeyValue',
+								properties: {
+									name: '={{$responseItem.modelName}}',
+									description: '={{$responseItem.modelArn}}',
+									value: '={{$responseItem.modelId}}',
+								},
+							},
+							{
+								type: 'sort',
+								properties: {
+									key: 'name',
+								},
+							},
+						],
+					},
+				},
+			},
+			additionalData,
+			PROVIDER_NODE_TYPE_MAP.awsBedrock,
+			{},
+			credentials,
+		);
+
+		const inferenceProfileModelsRequest = this.nodeParametersService.getOptionsViaLoadOptions(
+			{
+				routing: {
+					request: {
+						method: 'GET',
+						url: '/inference-profiles?maxResults=1000',
+					},
+					output: {
+						postReceive: [
+							{
+								type: 'rootProperty',
+								properties: {
+									property: 'inferenceProfileSummaries',
+								},
+							},
+							{
+								type: 'setKeyValue',
+								properties: {
+									name: '={{$responseItem.inferenceProfileName}}',
+									description:
+										'={{$responseItem.description || $responseItem.inferenceProfileArn}}',
+									value: '={{$responseItem.inferenceProfileId}}',
+								},
+							},
+							{
+								type: 'sort',
+								properties: {
+									key: 'name',
+								},
+							},
+						],
+					},
+				},
+			},
+			additionalData,
+			PROVIDER_NODE_TYPE_MAP.awsBedrock,
+			{},
+			credentials,
+		);
+
+		const [foundationModels, inferenceProfileModels] = await Promise.all([
+			foundationModelsRequest,
+			inferenceProfileModelsRequest,
+		]);
+
+		return foundationModels.concat(inferenceProfileModels);
+	}
+
+	private async fetchMistralCloudModels(
+		credentials: INodeCredentials,
+		additionalData: IWorkflowExecuteAdditionalData,
+	): Promise<INodePropertyOptions[]> {
+		return await this.nodeParametersService.getOptionsViaLoadOptions(
+			{
+				routing: {
+					request: {
+						method: 'GET',
+						url: '/models',
+					},
+					output: {
+						postReceive: [
+							{
+								type: 'rootProperty',
+								properties: {
+									property: 'data',
+								},
+							},
+							{
+								type: 'filter',
+								properties: {
+									pass: "={{ !$responseItem.id.includes('embed') }}",
+								},
+							},
+							{
+								type: 'setKeyValue',
+								properties: {
+									name: '={{ $responseItem.id }}',
+									value: '={{ $responseItem.id }}',
+								},
+							},
+							{
+								type: 'sort',
+								properties: {
+									key: 'name',
+								},
+							},
+						],
+					},
+				},
+			},
+			additionalData,
+			PROVIDER_NODE_TYPE_MAP.mistralCloud,
+			{},
+			credentials,
+		);
+	}
+
+	private async fetchCohereModels(
+		credentials: INodeCredentials,
+		additionalData: IWorkflowExecuteAdditionalData,
+	): Promise<INodePropertyOptions[]> {
+		return await this.nodeParametersService.getOptionsViaLoadOptions(
+			{
+				routing: {
+					request: {
+						method: 'GET',
+						url: '/v1/models?page_size=100&endpoint=chat',
+					},
+					output: {
+						postReceive: [
+							{
+								type: 'rootProperty',
+								properties: {
+									property: 'models',
+								},
+							},
+							{
+								type: 'setKeyValue',
+								properties: {
+									name: '={{$responseItem.name}}',
+									value: '={{$responseItem.name}}',
+									description: '={{$responseItem.description}}',
+								},
+							},
+							{
+								type: 'sort',
+								properties: {
+									key: 'name',
+								},
+							},
+						],
+					},
+				},
+			},
+			additionalData,
+			PROVIDER_NODE_TYPE_MAP.cohere,
+			{},
+			credentials,
+		);
+	}
+
+	private async fetchDeepSeekModels(
+		credentials: INodeCredentials,
+		additionalData: IWorkflowExecuteAdditionalData,
+	): Promise<INodePropertyOptions[]> {
+		return await this.nodeParametersService.getOptionsViaLoadOptions(
+			{
+				routing: {
+					request: {
+						method: 'GET',
+						url: '/models',
+					},
+					output: {
+						postReceive: [
+							{
+								type: 'rootProperty',
+								properties: {
+									property: 'data',
+								},
+							},
+							{
+								type: 'setKeyValue',
+								properties: {
+									name: '={{$responseItem.id}}',
+									value: '={{$responseItem.id}}',
+								},
+							},
+							{
+								type: 'sort',
+								properties: {
+									key: 'name',
+								},
+							},
+						],
+					},
+				},
+			},
+			additionalData,
+			PROVIDER_NODE_TYPE_MAP.deepSeek,
+			{},
+			credentials,
+		);
+	}
+
+	private async fetchOpenRouterModels(
+		credentials: INodeCredentials,
+		additionalData: IWorkflowExecuteAdditionalData,
+	): Promise<INodePropertyOptions[]> {
+		return await this.nodeParametersService.getOptionsViaLoadOptions(
+			{
+				routing: {
+					request: {
+						method: 'GET',
+						url: '/models',
+					},
+					output: {
+						postReceive: [
+							{
+								type: 'rootProperty',
+								properties: {
+									property: 'data',
+								},
+							},
+							{
+								type: 'setKeyValue',
+								properties: {
+									name: '={{$responseItem.id}}',
+									value: '={{$responseItem.id}}',
+								},
+							},
+							{
+								type: 'sort',
+								properties: {
+									key: 'name',
+								},
+							},
+						],
+					},
+				},
+			},
+			additionalData,
+			PROVIDER_NODE_TYPE_MAP.openRouter,
+			{},
+			credentials,
+		);
+	}
+
+	private async fetchGroqModels(
+		credentials: INodeCredentials,
+		additionalData: IWorkflowExecuteAdditionalData,
+	): Promise<INodePropertyOptions[]> {
+		return await this.nodeParametersService.getOptionsViaLoadOptions(
+			{
+				routing: {
+					request: {
+						method: 'GET',
+						url: '/models',
+					},
+					output: {
+						postReceive: [
+							{
+								type: 'rootProperty',
+								properties: {
+									property: 'data',
+								},
+							},
+							{
+								type: 'filter',
+								properties: {
+									pass: '={{ $responseItem.active === true && $responseItem.object === "model" }}',
+								},
+							},
+							{
+								type: 'setKeyValue',
+								properties: {
+									name: '={{$responseItem.id}}',
+									value: '={{$responseItem.id}}',
+								},
+							},
+						],
+					},
+				},
+			},
+			additionalData,
+			PROVIDER_NODE_TYPE_MAP.groq,
+			{},
+			credentials,
+		);
+	}
+
+	private async fetchXAiGrokModels(
+		credentials: INodeCredentials,
+		additionalData: IWorkflowExecuteAdditionalData,
+	): Promise<INodePropertyOptions[]> {
+		return await this.nodeParametersService.getOptionsViaLoadOptions(
+			{
+				routing: {
+					request: {
+						method: 'GET',
+						url: '/models',
+					},
+					output: {
+						postReceive: [
+							{
+								type: 'rootProperty',
+								properties: {
+									property: 'data',
+								},
+							},
+							{
+								type: 'setKeyValue',
+								properties: {
+									name: '={{$responseItem.id}}',
+									value: '={{$responseItem.id}}',
+								},
+							},
+							{
+								type: 'sort',
+								properties: {
+									key: 'name',
+								},
+							},
+						],
+					},
+				},
+			},
+			additionalData,
+			PROVIDER_NODE_TYPE_MAP.xAiGrok,
+			{},
+			credentials,
+		);
+	}
+
+	private async fetchVercelAiGatewayModels(
+		credentials: INodeCredentials,
+		additionalData: IWorkflowExecuteAdditionalData,
+	): Promise<INodePropertyOptions[]> {
+		return await this.nodeParametersService.getOptionsViaLoadOptions(
+			{
+				routing: {
+					request: {
+						method: 'GET',
+						url: '/models',
+					},
+					output: {
+						postReceive: [
+							{
+								type: 'rootProperty',
+								properties: {
+									property: 'data',
+								},
+							},
+							{
+								type: 'setKeyValue',
+								properties: {
+									name: '={{$responseItem.id}}',
+									value: '={{$responseItem.id}}',
+								},
+							},
+							{
+								type: 'sort',
+								properties: {
+									key: 'name',
+								},
+							},
+						],
+					},
+				},
+			},
+			additionalData,
+			PROVIDER_NODE_TYPE_MAP.vercelAiGateway,
+			{},
+			credentials,
+		);
+	}
+
+	private async fetchAgentWorkflowsAsModels(user: User): Promise<ChatModelsResponse['n8n']> {
+		// Workflows are scanned by their latest version for chat trigger nodes.
+		// This means that we might miss some active workflow versions that had chat triggers but
+		// the latest version does not, but this trade-off is done for performance.
+		const workflowsWithChatTrigger = await this.workflowService.getWorkflowsWithNodesIncluded(
+			user,
+			[CHAT_TRIGGER_NODE_TYPE],
+			true,
+		);
+
+		const activeWorkflows = workflowsWithChatTrigger
+			// Ensure the user has at least read access to the workflows
+			.filter((workflow) => workflow.scopes.includes('workflow:read'))
+			.filter((workflow) => !!workflow.activeVersionId);
+
+		const workflows = await this.workflowRepository.find({
+			select: { id: true },
+			where: { id: In(activeWorkflows.map((workflow) => workflow.id)) },
+			relations: { activeVersion: true },
+		});
+
+		const models: ChatModelDto[] = [];
+
+		for (const { id, activeVersion } of workflows) {
+			if (!activeVersion) {
+				continue;
+			}
+
+			const chatTrigger = activeVersion.nodes?.find((node) => node.type === CHAT_TRIGGER_NODE_TYPE);
+			if (!chatTrigger) {
+				continue;
+			}
+
+			const chatTriggerParams = validChatTriggerParamsShape.safeParse(chatTrigger.parameters).data;
+			if (!chatTriggerParams) {
+				continue;
+			}
+
+			const agentNodes = activeVersion.nodes?.filter(
+				(node) => node.type === AGENT_LANGCHAIN_NODE_TYPE,
+			);
+
+			// Agents older than this can't do streaming
+			if (agentNodes.some((node) => node.typeVersion < 2.1)) {
+				continue;
+			}
+
+			const inputModalities = this.chatHubWorkflowService.parseInputModalities(
+				chatTriggerParams.options,
+			);
+
+			models.push({
+				name: chatTriggerParams.agentName ?? activeVersion.name ?? 'Unknown Agent',
+				description: chatTriggerParams.agentDescription ?? null,
+				model: {
+					provider: 'n8n',
+					workflowId: id,
+				},
+				createdAt: activeVersion.createdAt ? activeVersion.createdAt.toISOString() : null,
+				updatedAt: activeVersion.updatedAt ? activeVersion.updatedAt.toISOString() : null,
+				metadata: {
+					inputModalities,
+					capabilities: {
+						functionCalling: false,
+					},
+				},
+			});
+		}
+
+		return {
+			models,
+		};
+	}
+
+	private transformAndFilterModels(
+		rawModels: INodePropertyOptions[],
+		provider: ChatHubLLMProvider,
+	): ChatModelDto[] {
+		return rawModels.map((model) => {
+			const id = String(model.value);
+
+			return {
+				id,
+				name: model.name,
+				description: model.description ?? null,
+				model: {
+					provider,
+					model: id,
+				},
+				createdAt: null,
+				updatedAt: null,
+				metadata: getModelMetadata(provider, id),
+			};
+		});
+	}
+}

packages/cli/src/modules/chat-hub/chat-hub.service.ts

@@ -2,7 +2,6 @@ import {
 	PROVIDER_CREDENTIAL_TYPE_MAP,
 	type ChatHubProvider,
 	type ChatHubLLMProvider,
-	type ChatModelsResponse,
 	type ChatHubConversationsResponse,
 	type ChatHubConversationResponse,
 	ChatHubMessageDto,
@@ -10,17 +9,14 @@ import {
 	type ChatSessionId,
 	ChatHubConversationModel,
 	ChatHubMessageStatus,
-	chatHubProviderSchema,
 	type EnrichedStructuredChunk,
 	ChatHubBaseLLMModel,
 	ChatHubN8nModel,
 	ChatHubCustomAgentModel,
-	emptyChatModelsResponse,
 	type ChatHubUpdateConversationRequest,
-	ChatModelDto,
 } from '@n8n/api-types';
 import { Logger } from '@n8n/backend-common';
-import { ExecutionRepository, IExecutionResponse, User, WorkflowRepository, In } from '@n8n/db';
+import { ExecutionRepository, IExecutionResponse, User, WorkflowRepository } from '@n8n/db';
 import { Service } from '@n8n/di';
 import type { EntityManager } from '@n8n/typeorm';
 import { GlobalConfig } from '@n8n/config';
@@ -32,7 +28,6 @@ import {
 	ManualExecutionCancelledError,
 	type INodeCredentials,
 	type IWorkflowBase,
-	type IWorkflowExecuteAdditionalData,
 	jsonParse,
 	jsonStringify,
 	StructuredChunk,
@@ -47,15 +42,11 @@ import {
 } from 'n8n-workflow';
 
 import { ActiveExecutions } from '@/active-executions';
-import { CredentialsFinderService } from '@/credentials/credentials-finder.service';
 import { BadRequestError } from '@/errors/response-errors/bad-request.error';
 import { NotFoundError } from '@/errors/response-errors/not-found.error';
 import { ExecutionService } from '@/executions/execution.service';
-import { DynamicNodeParametersService } from '@/services/dynamic-node-parameters.service';
-import { getBase } from '@/workflow-execute-additional-data';
 import { WorkflowExecutionService } from '@/workflows/workflow-execution.service';
 import { WorkflowFinderService } from '@/workflows/workflow-finder.service';
-import { WorkflowService } from '@/workflows/workflow.service';
 
 import { ChatHubAgentService } from './chat-hub-agent.service';
 import { ChatHubCredentialsService } from './chat-hub-credentials.service';
@@ -63,18 +54,12 @@ import type { ChatHubMessage } from './chat-hub-message.entity';
 import type { ChatHubSession } from './chat-hub-session.entity';
 import { ChatHubWorkflowService } from './chat-hub-workflow.service';
 import { ChatHubAttachmentService } from './chat-hub.attachment.service';
-import {
-	JSONL_STREAM_HEADERS,
-	NODE_NAMES,
-	PROVIDER_NODE_TYPE_MAP,
-	getModelMetadata,
-} from './chat-hub.constants';
+import { JSONL_STREAM_HEADERS, NODE_NAMES, PROVIDER_NODE_TYPE_MAP } from './chat-hub.constants';
 import { ChatHubSettingsService } from './chat-hub.settings.service';
 import {
 	HumanMessagePayload,
 	RegenerateMessagePayload,
 	EditMessagePayload,
-	validChatTriggerParamsShape,
 } from './chat-hub.types';
 import { ChatHubMessageRepository } from './chat-message.repository';
 import { ChatHubSessionRepository } from './chat-session.repository';
@@ -89,16 +74,13 @@ export class ChatHubService {
 		private readonly logger: Logger,
 		private readonly errorReporter: ErrorReporter,
 		private readonly executionService: ExecutionService,
-		private readonly nodeParametersService: DynamicNodeParametersService,
 		private readonly executionRepository: ExecutionRepository,
 		private readonly workflowExecutionService: WorkflowExecutionService,
-		private readonly workflowService: WorkflowService,
 		private readonly workflowFinderService: WorkflowFinderService,
 		private readonly workflowRepository: WorkflowRepository,
 		private readonly activeExecutions: ActiveExecutions,
 		private readonly sessionRepository: ChatHubSessionRepository,
 		private readonly messageRepository: ChatHubMessageRepository,
-		private readonly credentialsFinderService: CredentialsFinderService,
 		private readonly chatHubAgentService: ChatHubAgentService,
 		private readonly chatHubCredentialsService: ChatHubCredentialsService,
 		private readonly chatHubWorkflowService: ChatHubWorkflowService,
@@ -108,875 +90,6 @@ export class ChatHubService {
 		private readonly globalConfig: GlobalConfig,
 	) {}
 
-	async getModels(
-		user: User,
-		credentialIds: Record<ChatHubLLMProvider, string | null>,
-	): Promise<ChatModelsResponse> {
-		const additionalData = await getBase({ userId: user.id });
-		const providers = chatHubProviderSchema.options;
-
-		const allCredentials = await this.credentialsFinderService.findCredentialsForUser(user, [
-			'credential:read',
-		]);
-
-		const responses = await Promise.all(
-			providers.map<Promise<[ChatHubProvider, ChatModelsResponse[ChatHubProvider]]>>(
-				async (provider: ChatHubProvider) => {
-					const credentials: INodeCredentials = {};
-
-					if (provider !== 'n8n' && provider !== 'custom-agent') {
-						const credentialId = credentialIds[provider];
-						if (!credentialId) {
-							return [provider, { models: [] }];
-						}
-
-						// Ensure the user has the permission to read the credential
-						if (!allCredentials.some((credential) => credential.id === credentialId)) {
-							return [
-								provider,
-								{ models: [], error: 'Could not retrieve models. Verify credentials.' },
-							];
-						}
-
-						credentials[PROVIDER_CREDENTIAL_TYPE_MAP[provider]] = { name: '', id: credentialId };
-					}
-
-					try {
-						return [
-							provider,
-							await this.fetchModelsForProvider(user, provider, credentials, additionalData),
-						];
-					} catch {
-						return [
-							provider,
-							{ models: [], error: 'Could not retrieve models. Verify credentials.' },
-						];
-					}
-				},
-			),
-		);
-
-		return responses.reduce<ChatModelsResponse>(
-			(acc, [provider, res]) => {
-				acc[provider] = res;
-				return acc;
-			},
-			{ ...emptyChatModelsResponse },
-		);
-	}
-
-	private async fetchModelsForProvider(
-		user: User,
-		provider: ChatHubProvider,
-		credentials: INodeCredentials,
-		additionalData: IWorkflowExecuteAdditionalData,
-	): Promise<ChatModelsResponse[ChatHubProvider]> {
-		switch (provider) {
-			case 'openai':
-				return await this.fetchOpenAiModels(credentials, additionalData);
-			case 'anthropic':
-				return await this.fetchAnthropicModels(credentials, additionalData);
-			case 'google':
-				return await this.fetchGoogleModels(credentials, additionalData);
-			case 'ollama':
-				return await this.fetchOllamaModels(credentials, additionalData);
-			case 'azureOpenAi':
-			case 'azureEntraId':
-				return this.fetchAzureOpenAiModels(credentials, additionalData);
-			case 'awsBedrock':
-				return await this.fetchAwsBedrockModels(credentials, additionalData);
-			case 'vercelAiGateway':
-				return await this.fetchVercelAiGatewayModels(credentials, additionalData);
-			case 'xAiGrok':
-				return await this.fetchXAiGrokModels(credentials, additionalData);
-			case 'groq':
-				return await this.fetchGroqModels(credentials, additionalData);
-			case 'openRouter':
-				return await this.fetchOpenRouterModels(credentials, additionalData);
-			case 'deepSeek':
-				return await this.fetchDeepSeekModels(credentials, additionalData);
-			case 'cohere':
-				return await this.fetchCohereModels(credentials, additionalData);
-			case 'mistralCloud':
-				return await this.fetchMistralCloudModels(credentials, additionalData);
-			case 'n8n':
-				return await this.fetchAgentWorkflowsAsModels(user);
-			case 'custom-agent':
-				return await this.chatHubAgentService.getAgentsByUserIdAsModels(user.id);
-		}
-	}
-
-	private async fetchOpenAiModels(
-		credentials: INodeCredentials,
-		additionalData: IWorkflowExecuteAdditionalData,
-	): Promise<ChatModelsResponse['openai']> {
-		const resourceLocatorResults = await this.nodeParametersService.getResourceLocatorResults(
-			'searchModels',
-			'parameters.model',
-			additionalData,
-			PROVIDER_NODE_TYPE_MAP.openai,
-			{},
-			credentials,
-		);
-
-		return {
-			models: resourceLocatorResults.results.map((result) => ({
-				name: result.name,
-				description: result.description ?? null,
-				model: {
-					provider: 'openai',
-					model: String(result.value),
-				},
-				createdAt: null,
-				updatedAt: null,
-				metadata: getModelMetadata('openai', String(result.value)),
-			})),
-		};
-	}
-
-	private async fetchAnthropicModels(
-		credentials: INodeCredentials,
-		additionalData: IWorkflowExecuteAdditionalData,
-	): Promise<ChatModelsResponse['anthropic']> {
-		const resourceLocatorResults = await this.nodeParametersService.getResourceLocatorResults(
-			'searchModels',
-			'parameters.model',
-			additionalData,
-			PROVIDER_NODE_TYPE_MAP.anthropic,
-			{},
-			credentials,
-		);
-
-		return {
-			models: resourceLocatorResults.results.map((result) => ({
-				name: result.name,
-				description: result.description ?? null,
-				model: {
-					provider: 'anthropic',
-					model: String(result.value),
-				},
-				createdAt: null,
-				updatedAt: null,
-				metadata: getModelMetadata('anthropic', String(result.value)),
-			})),
-		};
-	}
-
-	private async fetchGoogleModels(
-		credentials: INodeCredentials,
-		additionalData: IWorkflowExecuteAdditionalData,
-	): Promise<ChatModelsResponse['google']> {
-		const results = await this.nodeParametersService.getOptionsViaLoadOptions(
-			{
-				// From Gemini node
-				// https://github.com/n8n-io/n8n/blob/master/packages/%40n8n/nodes-langchain/nodes/llms/LmChatGoogleGemini/LmChatGoogleGemini.node.ts#L75
-				routing: {
-					request: {
-						method: 'GET',
-						url: '/v1beta/models',
-					},
-					output: {
-						postReceive: [
-							{
-								type: 'rootProperty',
-								properties: {
-									property: 'models',
-								},
-							},
-							{
-								type: 'filter',
-								properties: {
-									pass: "={{ !$responseItem.name.includes('embedding') }}",
-								},
-							},
-							{
-								type: 'setKeyValue',
-								properties: {
-									name: '={{$responseItem.name}}',
-									value: '={{$responseItem.name}}',
-									description: '={{$responseItem.description}}',
-								},
-							},
-							{
-								type: 'sort',
-								properties: {
-									key: 'name',
-								},
-							},
-						],
-					},
-				},
-			},
-			additionalData,
-			PROVIDER_NODE_TYPE_MAP.google,
-			{},
-			credentials,
-		);
-
-		return {
-			models: results.map((result) => ({
-				name: result.name,
-				description: result.description ?? null,
-				model: {
-					provider: 'google',
-					model: String(result.value),
-				},
-				createdAt: null,
-				updatedAt: null,
-				metadata: getModelMetadata('google', String(result.value)),
-			})),
-		};
-	}
-
-	private async fetchOllamaModels(
-		credentials: INodeCredentials,
-		additionalData: IWorkflowExecuteAdditionalData,
-	): Promise<ChatModelsResponse['ollama']> {
-		const results = await this.nodeParametersService.getOptionsViaLoadOptions(
-			{
-				// From Ollama Model node
-				// https://github.com/n8n-io/n8n/blob/master/packages/%40n8n/nodes-langchain/nodes/llms/LMOllama/description.ts#L24
-				routing: {
-					request: {
-						method: 'GET',
-						url: '/api/tags',
-					},
-					output: {
-						postReceive: [
-							{
-								type: 'rootProperty',
-								properties: {
-									property: 'models',
-								},
-							},
-							{
-								type: 'setKeyValue',
-								properties: {
-									name: '={{$responseItem.name}}',
-									value: '={{$responseItem.name}}',
-								},
-							},
-							{
-								type: 'sort',
-								properties: {
-									key: 'name',
-								},
-							},
-						],
-					},
-				},
-			},
-			additionalData,
-			PROVIDER_NODE_TYPE_MAP.ollama,
-			{},
-			credentials,
-		);
-
-		return {
-			models: results.map((result) => ({
-				name: result.name,
-				description: result.description ?? null,
-				model: {
-					provider: 'ollama',
-					model: String(result.value),
-				},
-				createdAt: null,
-				updatedAt: null,
-				metadata: getModelMetadata('ollama', String(result.value)),
-			})),
-		};
-	}
-
-	private fetchAzureOpenAiModels(
-		_credentials: INodeCredentials,
-		_additionalData: IWorkflowExecuteAdditionalData,
-	): ChatModelsResponse['azureOpenAi'] {
-		// Azure doesn't appear to offer a way to list available models via API.
-		// If we add support for this in the future on the Azure OpenAI node we should copy that
-		// implementation here too.
-		return {
-			models: [],
-		};
-	}
-
-	private async fetchAwsBedrockModels(
-		credentials: INodeCredentials,
-		additionalData: IWorkflowExecuteAdditionalData,
-	): Promise<ChatModelsResponse['awsBedrock']> {
-		// From AWS Bedrock node
-		// https://github.com/n8n-io/n8n/blob/master/packages/%40n8n/nodes-langchain/nodes/llms/LmChatAwsBedrock/LmChatAwsBedrock.node.ts#L100
-		// https://github.com/n8n-io/n8n/blob/master/packages/%40n8n/nodes-langchain/nodes/llms/LmChatAwsBedrock/LmChatAwsBedrock.node.ts#L155
-		const foundationModelsRequest = this.nodeParametersService.getOptionsViaLoadOptions(
-			{
-				routing: {
-					request: {
-						method: 'GET',
-						url: '/foundation-models?&byOutputModality=TEXT&byInferenceType=ON_DEMAND',
-					},
-					output: {
-						postReceive: [
-							{
-								type: 'rootProperty',
-								properties: {
-									property: 'modelSummaries',
-								},
-							},
-							{
-								type: 'setKeyValue',
-								properties: {
-									name: '={{$responseItem.modelName}}',
-									description: '={{$responseItem.modelArn}}',
-									value: '={{$responseItem.modelId}}',
-								},
-							},
-							{
-								type: 'sort',
-								properties: {
-									key: 'name',
-								},
-							},
-						],
-					},
-				},
-			},
-			additionalData,
-			PROVIDER_NODE_TYPE_MAP.awsBedrock,
-			{},
-			credentials,
-		);
-
-		const inferenceProfileModelsRequest = this.nodeParametersService.getOptionsViaLoadOptions(
-			{
-				routing: {
-					request: {
-						method: 'GET',
-						url: '/inference-profiles?maxResults=1000',
-					},
-					output: {
-						postReceive: [
-							{
-								type: 'rootProperty',
-								properties: {
-									property: 'inferenceProfileSummaries',
-								},
-							},
-							{
-								type: 'setKeyValue',
-								properties: {
-									name: '={{$responseItem.inferenceProfileName}}',
-									description:
-										'={{$responseItem.description || $responseItem.inferenceProfileArn}}',
-									value: '={{$responseItem.inferenceProfileId}}',
-								},
-							},
-							{
-								type: 'sort',
-								properties: {
-									key: 'name',
-								},
-							},
-						],
-					},
-				},
-			},
-			additionalData,
-			PROVIDER_NODE_TYPE_MAP.awsBedrock,
-			{},
-			credentials,
-		);
-
-		const [foundationModels, inferenceProfileModels] = await Promise.all([
-			foundationModelsRequest,
-			inferenceProfileModelsRequest,
-		]);
-
-		return {
-			models: foundationModels.concat(inferenceProfileModels).map((result) => ({
-				name: result.name,
-				description: result.description ?? String(result.value),
-				model: {
-					provider: 'awsBedrock',
-					model: String(result.value),
-				},
-				createdAt: null,
-				updatedAt: null,
-				metadata: getModelMetadata('awsBedrock', String(result.value)),
-			})),
-		};
-	}
-
-	private async fetchMistralCloudModels(
-		credentials: INodeCredentials,
-		additionalData: IWorkflowExecuteAdditionalData,
-	): Promise<ChatModelsResponse['mistralCloud']> {
-		const results = await this.nodeParametersService.getOptionsViaLoadOptions(
-			{
-				routing: {
-					request: {
-						method: 'GET',
-						url: '/models',
-					},
-					output: {
-						postReceive: [
-							{
-								type: 'rootProperty',
-								properties: {
-									property: 'data',
-								},
-							},
-							{
-								type: 'filter',
-								properties: {
-									pass: "={{ !$responseItem.id.includes('embed') }}",
-								},
-							},
-							{
-								type: 'setKeyValue',
-								properties: {
-									name: '={{ $responseItem.id }}',
-									value: '={{ $responseItem.id }}',
-								},
-							},
-							{
-								type: 'sort',
-								properties: {
-									key: 'name',
-								},
-							},
-						],
-					},
-				},
-			},
-			additionalData,
-			PROVIDER_NODE_TYPE_MAP.mistralCloud,
-			{},
-			credentials,
-		);
-
-		return {
-			models: results.map((result) => ({
-				name: result.name,
-				description: result.description ?? String(result.value),
-				model: {
-					provider: 'mistralCloud',
-					model: String(result.value),
-				},
-				createdAt: null,
-				updatedAt: null,
-				metadata: getModelMetadata('mistralCloud', String(result.value)),
-			})),
-		};
-	}
-
-	private async fetchCohereModels(
-		credentials: INodeCredentials,
-		additionalData: IWorkflowExecuteAdditionalData,
-	): Promise<ChatModelsResponse['cohere']> {
-		const results = await this.nodeParametersService.getOptionsViaLoadOptions(
-			{
-				routing: {
-					request: {
-						method: 'GET',
-						url: '/v1/models?page_size=100&endpoint=chat',
-					},
-					output: {
-						postReceive: [
-							{
-								type: 'rootProperty',
-								properties: {
-									property: 'models',
-								},
-							},
-							{
-								type: 'setKeyValue',
-								properties: {
-									name: '={{$responseItem.name}}',
-									value: '={{$responseItem.name}}',
-									description: '={{$responseItem.description}}',
-								},
-							},
-							{
-								type: 'sort',
-								properties: {
-									key: 'name',
-								},
-							},
-						],
-					},
-				},
-			},
-			additionalData,
-			PROVIDER_NODE_TYPE_MAP.cohere,
-			{},
-			credentials,
-		);
-
-		return {
-			models: results.map((result) => ({
-				name: result.name,
-				description: result.description ?? null,
-				model: {
-					provider: 'cohere',
-					model: String(result.value),
-				},
-				createdAt: null,
-				updatedAt: null,
-				metadata: getModelMetadata('cohere', String(result.value)),
-			})),
-		};
-	}
-
-	private async fetchDeepSeekModels(
-		credentials: INodeCredentials,
-		additionalData: IWorkflowExecuteAdditionalData,
-	): Promise<ChatModelsResponse['deepSeek']> {
-		const results = await this.nodeParametersService.getOptionsViaLoadOptions(
-			{
-				routing: {
-					request: {
-						method: 'GET',
-						url: '/models',
-					},
-					output: {
-						postReceive: [
-							{
-								type: 'rootProperty',
-								properties: {
-									property: 'data',
-								},
-							},
-							{
-								type: 'setKeyValue',
-								properties: {
-									name: '={{$responseItem.id}}',
-									value: '={{$responseItem.id}}',
-								},
-							},
-							{
-								type: 'sort',
-								properties: {
-									key: 'name',
-								},
-							},
-						],
-					},
-				},
-			},
-			additionalData,
-			PROVIDER_NODE_TYPE_MAP.deepSeek,
-			{},
-			credentials,
-		);
-
-		return {
-			models: results.map((result) => ({
-				name: result.name,
-				description: result.description ?? String(result.value),
-				model: {
-					provider: 'deepSeek',
-					model: String(result.value),
-				},
-				createdAt: null,
-				updatedAt: null,
-				metadata: getModelMetadata('deepSeek', String(result.value)),
-			})),
-		};
-	}
-
-	private async fetchOpenRouterModels(
-		credentials: INodeCredentials,
-		additionalData: IWorkflowExecuteAdditionalData,
-	): Promise<ChatModelsResponse['openRouter']> {
-		const results = await this.nodeParametersService.getOptionsViaLoadOptions(
-			{
-				routing: {
-					request: {
-						method: 'GET',
-						url: '/models',
-					},
-					output: {
-						postReceive: [
-							{
-								type: 'rootProperty',
-								properties: {
-									property: 'data',
-								},
-							},
-							{
-								type: 'setKeyValue',
-								properties: {
-									name: '={{$responseItem.id}}',
-									value: '={{$responseItem.id}}',
-								},
-							},
-							{
-								type: 'sort',
-								properties: {
-									key: 'name',
-								},
-							},
-						],
-					},
-				},
-			},
-			additionalData,
-			PROVIDER_NODE_TYPE_MAP.openRouter,
-			{},
-			credentials,
-		);
-
-		return {
-			models: results.map((result) => ({
-				name: result.name,
-				description: result.description ?? null,
-				model: {
-					provider: 'openRouter',
-					model: String(result.value),
-				},
-				createdAt: null,
-				updatedAt: null,
-				metadata: getModelMetadata('openRouter', String(result.value)),
-			})),
-		};
-	}
-
-	private async fetchGroqModels(
-		credentials: INodeCredentials,
-		additionalData: IWorkflowExecuteAdditionalData,
-	): Promise<ChatModelsResponse['groq']> {
-		const results = await this.nodeParametersService.getOptionsViaLoadOptions(
-			{
-				routing: {
-					request: {
-						method: 'GET',
-						url: '/models',
-					},
-					output: {
-						postReceive: [
-							{
-								type: 'rootProperty',
-								properties: {
-									property: 'data',
-								},
-							},
-							{
-								type: 'filter',
-								properties: {
-									pass: '={{ $responseItem.active === true && $responseItem.object === "model" }}',
-								},
-							},
-							{
-								type: 'setKeyValue',
-								properties: {
-									name: '={{$responseItem.id}}',
-									value: '={{$responseItem.id}}',
-								},
-							},
-						],
-					},
-				},
-			},
-			additionalData,
-			PROVIDER_NODE_TYPE_MAP.groq,
-			{},
-			credentials,
-		);
-
-		return {
-			models: results.map((result) => ({
-				name: result.name,
-				description: result.description ?? null,
-				model: {
-					provider: 'groq',
-					model: String(result.value),
-				},
-				createdAt: null,
-				updatedAt: null,
-				metadata: getModelMetadata('groq', String(result.value)),
-			})),
-		};
-	}
-
-	private async fetchXAiGrokModels(
-		credentials: INodeCredentials,
-		additionalData: IWorkflowExecuteAdditionalData,
-	): Promise<ChatModelsResponse['xAiGrok']> {
-		const results = await this.nodeParametersService.getOptionsViaLoadOptions(
-			{
-				routing: {
-					request: {
-						method: 'GET',
-						url: '/models',
-					},
-					output: {
-						postReceive: [
-							{
-								type: 'rootProperty',
-								properties: {
-									property: 'data',
-								},
-							},
-							{
-								type: 'setKeyValue',
-								properties: {
-									name: '={{$responseItem.id}}',
-									value: '={{$responseItem.id}}',
-								},
-							},
-							{
-								type: 'sort',
-								properties: {
-									key: 'name',
-								},
-							},
-						],
-					},
-				},
-			},
-			additionalData,
-			PROVIDER_NODE_TYPE_MAP.xAiGrok,
-			{},
-			credentials,
-		);
-
-		return {
-			models: results.map((result) => ({
-				name: result.name,
-				description: result.description ?? null,
-				model: {
-					provider: 'xAiGrok',
-					model: String(result.value),
-				},
-				createdAt: null,
-				updatedAt: null,
-				metadata: getModelMetadata('xAiGrok', String(result.value)),
-			})),
-		};
-	}
-
-	private async fetchVercelAiGatewayModels(
-		credentials: INodeCredentials,
-		additionalData: IWorkflowExecuteAdditionalData,
-	): Promise<ChatModelsResponse['vercelAiGateway']> {
-		const results = await this.nodeParametersService.getOptionsViaLoadOptions(
-			{
-				routing: {
-					request: {
-						method: 'GET',
-						url: '/models',
-					},
-					output: {
-						postReceive: [
-							{
-								type: 'rootProperty',
-								properties: {
-									property: 'data',
-								},
-							},
-							{
-								type: 'setKeyValue',
-								properties: {
-									name: '={{$responseItem.id}}',
-									value: '={{$responseItem.id}}',
-								},
-							},
-							{
-								type: 'sort',
-								properties: {
-									key: 'name',
-								},
-							},
-						],
-					},
-				},
-			},
-			additionalData,
-			PROVIDER_NODE_TYPE_MAP.vercelAiGateway,
-			{},
-			credentials,
-		);
-
-		return {
-			models: results.map((result) => ({
-				name: result.name,
-				description: result.description ?? String(result.value),
-				model: {
-					provider: 'vercelAiGateway',
-					model: String(result.value),
-				},
-				createdAt: null,
-				updatedAt: null,
-				metadata: getModelMetadata('vercelAiGateway', String(result.value)),
-			})),
-		};
-	}
-
-	private async fetchAgentWorkflowsAsModels(user: User): Promise<ChatModelsResponse['n8n']> {
-		// Workflows are scanned by their latest version for chat trigger nodes.
-		// This means that we might miss some active workflow versions that had chat triggers but
-		// the latest version does not, but this trade-off is done for performance.
-		const workflowsWithChatTrigger = await this.workflowService.getWorkflowsWithNodesIncluded(
-			user,
-			[CHAT_TRIGGER_NODE_TYPE],
-			true,
-		);
-
-		const activeWorkflows = workflowsWithChatTrigger
-			// Ensure the user has at least read access to the workflows
-			.filter((workflow) => workflow.scopes.includes('workflow:read'))
-			.filter((workflow) => !!workflow.activeVersionId);
-
-		const workflows = await this.workflowRepository.find({
-			select: { id: true },
-			where: { id: In(activeWorkflows.map((workflow) => workflow.id)) },
-			relations: { activeVersion: true },
-		});
-
-		const models: ChatModelDto[] = [];
-
-		for (const { id, activeVersion } of workflows) {
-			if (!activeVersion) {
-				continue;
-			}
-
-			const chatTrigger = activeVersion.nodes?.find((node) => node.type === CHAT_TRIGGER_NODE_TYPE);
-
-			if (!chatTrigger) {
-				continue;
-			}
-
-			const chatTriggerParams = validChatTriggerParamsShape.safeParse(chatTrigger.parameters).data;
-			if (!chatTriggerParams) {
-				continue;
-			}
-
-			const inputModalities = this.chatHubWorkflowService.parseInputModalities(
-				chatTriggerParams.options,
-			);
-
-			models.push({
-				name: chatTriggerParams.agentName ?? activeVersion.name ?? 'Unknown Agent',
-				description: chatTriggerParams.agentDescription ?? null,
-				model: {
-					provider: 'n8n',
-					workflowId: id,
-				},
-				createdAt: activeVersion.createdAt ? activeVersion.createdAt.toISOString() : null,
-				updatedAt: activeVersion.updatedAt ? activeVersion.updatedAt.toISOString() : null,
-				metadata: {
-					inputModalities,
-					capabilities: {
-						functionCalling: false,
-					},
-				},
-			});
-		}
-
-		return {
-			models,
-		};
-	}
-
 	private async deleteChatWorkflow(workflowId: string): Promise<void> {
 		await this.workflowRepository.delete(workflowId);
 	}