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

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+# n8n Workflow Comparison
+
+Graph-based workflow similarity comparison using NetworkX and graph edit distance.
+
+## Features
+
+- **Graph Edit Distance**: Uses NetworkX's graph edit distance algorithm for accurate structural comparison
+- **Configurable Cost Functions**: Customize costs for different types of edits (node/edge insertion, deletion, substitution)
+- **Special Case Handling**: Higher penalties for trigger mismatches, similar node types grouped together
+- **Parameter Comparison**: Deep comparison of node parameters with configurable ignore rules
+- **External Configuration**: YAML/JSON config files for easy customization without code changes ([see CONFIGURATION.md](CONFIGURATION.md))
+- **Built-in Presets**: Strict, standard, and lenient comparison modes
+- **Detailed Output**: Returns similarity score and top edit operations needed
+
+## Installation
+
+This module uses `uv` for dependency management. No installation is needed - dependencies are automatically managed by `uvx`.
+
+### Prerequisites
+
+Install `uv`:
+
+```bash
+# macOS/Linux
+curl -LsSf https://astral.sh/uv/install.sh | sh
+
+# Windows
+powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
+```
+
+Install [just](https://github.com/casey/just)
+```bash
+# on macOS via homebrew
+brew install just
+# or gloabl install via NPM
+npm install -g rust-just
+# or cross platform via curl to DEST
+curl --proto '=https' --tlsv1.2 -sSf https://just.systems/install.sh | bash -s -- --to DEST
+
+```
+
+
+## Usage
+
+### CLI Usage
+
+```bash
+# Using default (standard) configuration
+uvx --from . python -m src.compare_workflows generated.json ground_truth.json
+
+# Using a preset
+uvx --from . python -m src.compare_workflows generated.json ground_truth.json --preset strict
+
+# Using custom configuration
+uvx --from . python -m src.compare_workflows generated.json ground_truth.json --config my-config.yaml
+
+# Output as human-readable summary
+uvx --from . python -m src.compare_workflows generated.json ground_truth.json --output-format summary
+```
+
+### Python API Usage
+
+```python
+from config_loader import load_config
+from graph_builder import build_workflow_graph
+from similarity import calculate_graph_edit_distance
+import json
+
+# Load workflows
+with open('generated.json') as f:
+    generated = json.load(f)
+with open('ground_truth.json') as f:
+    ground_truth = json.load(f)
+
+# Load configuration
+config = load_config('preset:standard')
+
+# Build graphs
+g1 = build_workflow_graph(generated, config)
+g2 = build_workflow_graph(ground_truth, config)
+
+# Calculate similarity
+result = calculate_graph_edit_distance(g1, g2, config)
+
+print(f"Similarity: {result['similarity_score']:.2%}")
+print(f"Edit cost: {result['edit_cost']:.1f}")
+print(f"Top edits: {len(result['top_edits'])}")
+```
+
+## Configuration
+
+> **📖 For detailed configuration documentation, see [CONFIGURATION.md](CONFIGURATION.md)**
+
+### Built-in Presets
+
+- **strict**: High penalties, exact matching required
+- **standard**: Balanced comparison (default)
+- **lenient**: Low penalties, focus on structure over details
+
+### Quick Start
+
+Create a YAML or JSON file with your custom rules:
+
+```yaml
+version: "1.0"
+name: "my-custom-config"
+description: "Custom configuration for my use case"
+
+costs:
+  nodes:
+    insertion: 10.0
+    deletion: 10.0
+    substitution:
+      same_type: 1.0
+      similar_type: 5.0
+      different_type: 15.0
+      trigger_mismatch: 50.0
+
+  edges:
+    insertion: 5.0
+    deletion: 5.0
+    substitution: 3.0
+
+similarity_groups:
+  triggers:
+    - "n8n-nodes-base.webhook"
+    - "n8n-nodes-base.manualTrigger"
+
+ignore:
+  node_types:
+    - "n8n-nodes-base.stickyNote"
+  global_parameters:
+    - "position"
+    - "id"
+
+parameter_comparison:
+  numeric_tolerance:
+    - parameter: "options.temperature"
+      tolerance: 0.1
+      cost_if_exceeded: 2.0
+```
+
+**For comprehensive documentation including:**
+- Complete field reference
+- Cost configuration strategies
+- Advanced ignore rules and wildcards
+- Parameter comparison rules
+- Exemptions and conditional logic
+- Real-world examples
+
+See **[CONFIGURATION.md](CONFIGURATION.md)**
+
+## Output Format
+
+### JSON Output
+
+```json
+{
+  "similarity_score": 0.78,
+  "similarity_percentage": "78.0%",
+  "edit_cost": 45.0,
+  "max_possible_cost": 205.0,
+  "top_edits": [
+    {
+      "type": "node_substitute",
+      "description": "Replace 'Manual Trigger' with 'Webhook Trigger'",
+      "cost": 25.0,
+      "priority": "critical"
+    }
+  ],
+  "metadata": {
+    "generated_nodes": 5,
+    "ground_truth_nodes": 6
+  }
+}
+```
+
+### Summary Output
+
+```
+============================================================
+WORKFLOW COMPARISON SUMMARY
+============================================================
+
+Overall Similarity: 78.0%
+Edit Cost:          45.0 / 205.0
+
+Configuration: standard
+  Standard balanced comparison configuration
+
+Top 3 Required Edits:
+------------------------------------------------------------
+1. 🔴 [CRITICAL] Cost: 25.0
+   Replace 'Manual Trigger' with 'Webhook Trigger'
+
+2. 🟠 [MAJOR] Cost: 10.0
+   Add missing 'HTTP Request' tool node
+
+3. 🟡 [MINOR] Cost: 5.0
+   Remove connection from 'Agent' to 'Extra Node'
+
+============================================================
+✅ PASS - Workflows are sufficiently similar
+============================================================
+```
+
+## Testing
+
+Run the test suite:
+
+```bash
+# Install dev dependencies
+uv sync --dev
+
+# Run tests
+uv run pytest
+
+# Run with coverage
+uv run pytest --cov
+```
+
+## Algorithm Details
+
+### Graph Representation
+- Each workflow node becomes a graph node with attributes (type, parameters, etc.)
+- Node and edge get a generated ID based on their position in the workflow
+- Each workflow connection becomes a directed edge with connection type
+- Nodes and edges are filtered based on configuration rules
+
+### Graph Edit Distance
+Uses NetworkX's `optimize_graph_edit_distance` with custom cost functions:
+- Node operations: insertion, deletion, substitution
+- Edge operations: insertion, deletion, substitution
+- Cost functions consider node types, parameters, and configuration rules
+
+### Similarity Score
+```
+similarity = 1 - (edit_cost / max_possible_cost)
+```
+
+Where `max_possible_cost` is the cost of deleting all nodes/edges from g1 and inserting all from g2.
+
+## Troubleshooting
+
+### Timeout errors
+For very large or complex workflows, the comparison may timeout. Consider:
+- Using a lenient preset to reduce computation
+- Simplifying the workflow structure
+- Increasing the timeout in the TypeScript wrapper
+
+### Configuration errors
+- Ensure YAML/JSON syntax is valid
+- Check that node types and parameter paths are correct
+- Use `--verbose` flag to see detailed configuration info

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/example_workflows/generated.json

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+{
+	"name": "Simple Test Workflow",
+	"nodes": [
+		{
+			"id": "1",
+			"name": "Webhook Trigger",
+			"type": "n8n-nodes-base.webhook",
+			"typeVersion": 1,
+			"position": [250, 300],
+			"parameters": {
+				"path": "/test"
+			}
+		},
+		{
+			"id": "2",
+			"name": "Code",
+			"type": "n8n-nodes-base.code",
+			"typeVersion": 1,
+			"position": [450, 300],
+			"parameters": {
+				"jsCode": "return items;"
+			}
+		}
+	],
+	"connections": {
+		"Webhook Trigger": {
+			"main": [
+				[
+					{
+						"node": "Code",
+						"type": "main",
+						"index": 0
+					}
+				]
+			]
+		}
+	}
+}

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/example_workflows/generated_wrong.json

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+{
+	"name": "Simple Test Workflow",
+	"nodes": [
+		{
+			"id": "1",
+			"name": "Webhook Trigger 2",
+			"type": "n8n-nodes-base.webhook",
+			"typeVersion": 1,
+			"position": [250, 300],
+			"parameters": {
+				"path": "/test2"
+			}
+		},
+		{
+			"id": "2",
+			"name": "Code",
+			"type": "n8n-nodes-base.code",
+			"typeVersion": 1,
+			"position": [450, 300],
+			"parameters": {
+				"jsCode": "return items.map(item => item.name);"
+			}
+		}
+	],
+	"connections": {
+		"Webhook Trigger 2": {
+			"main": [
+				[
+					{
+						"node": "Code",
+						"type": "main",
+						"index": 0
+					}
+				]
+			]
+		}
+	}
+}

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/example_workflows/multi_trigger.json

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+{
+	"name": "Multi-Trigger Workflow",
+	"nodes": [
+		{
+			"id": "1",
+			"name": "Webhook Trigger",
+			"type": "n8n-nodes-base.webhook",
+			"typeVersion": 1,
+			"position": [250, 300],
+			"parameters": {
+				"path": "/webhook1"
+			}
+		},
+		{
+			"id": "2",
+			"name": "Schedule Trigger",
+			"type": "n8n-nodes-base.scheduleTrigger",
+			"typeVersion": 1,
+			"position": [250, 450],
+			"parameters": {
+				"rule": {
+					"interval": [
+						{
+							"field": "hours",
+							"hoursInterval": 1
+						}
+					]
+				}
+			}
+		},
+		{
+			"id": "3",
+			"name": "Merge",
+			"type": "n8n-nodes-base.merge",
+			"typeVersion": 1,
+			"position": [450, 375],
+			"parameters": {}
+		},
+		{
+			"id": "4",
+			"name": "Process Data",
+			"type": "n8n-nodes-base.code",
+			"typeVersion": 1,
+			"position": [650, 375],
+			"parameters": {
+				"jsCode": "return items;"
+			}
+		}
+	],
+	"connections": {
+		"Webhook Trigger": {
+			"main": [
+				[
+					{
+						"node": "Merge",
+						"type": "main",
+						"index": 0
+					}
+				]
+			]
+		},
+		"Schedule Trigger": {
+			"main": [
+				[
+					{
+						"node": "Merge",
+						"type": "main",
+						"index": 1
+					}
+				]
+			]
+		},
+		"Merge": {
+			"main": [
+				[
+					{
+						"node": "Process Data",
+						"type": "main",
+						"index": 0
+					}
+				]
+			]
+		}
+	}
+}

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/example_workflows/multi_trigger_different_order.json

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+{
+	"name": "Multi-Trigger Workflow Different Order",
+	"nodes": [
+		{
+			"id": "4",
+			"name": "Process Data Node",
+			"type": "n8n-nodes-base.code",
+			"typeVersion": 1,
+			"position": [650, 375],
+			"parameters": {
+				"jsCode": "return items;"
+			}
+		},
+		{
+			"id": "2",
+			"name": "Schedule Trigger Different",
+			"type": "n8n-nodes-base.scheduleTrigger",
+			"typeVersion": 1,
+			"position": [250, 450],
+			"parameters": {
+				"rule": {
+					"interval": [
+						{
+							"field": "hours",
+							"hoursInterval": 1
+						}
+					]
+				}
+			}
+		},
+		{
+			"id": "3",
+			"name": "Merge Node",
+			"type": "n8n-nodes-base.merge",
+			"typeVersion": 1,
+			"position": [450, 375],
+			"parameters": {}
+		},
+		{
+			"id": "1",
+			"name": "Webhook Trigger Different",
+			"type": "n8n-nodes-base.webhook",
+			"typeVersion": 1,
+			"position": [250, 300],
+			"parameters": {
+				"path": "/webhook1"
+			}
+		}
+	],
+	"connections": {
+		"Webhook Trigger Different": {
+			"main": [
+				[
+					{
+						"node": "Merge Node",
+						"type": "main",
+						"index": 0
+					}
+				]
+			]
+		},
+		"Schedule Trigger Different": {
+			"main": [
+				[
+					{
+						"node": "Merge Node",
+						"type": "main",
+						"index": 1
+					}
+				]
+			]
+		},
+		"Merge Node": {
+			"main": [
+				[
+					{
+						"node": "Process Data Node",
+						"type": "main",
+						"index": 0
+					}
+				]
+			]
+		}
+	}
+}

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/example_workflows/multi_trigger_missing_node.json

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+{
+	"name": "Multi-Trigger Workflow Missing Merge",
+	"nodes": [
+		{
+			"id": "1",
+			"name": "HTTP Trigger",
+			"type": "n8n-nodes-base.webhook",
+			"typeVersion": 1,
+			"position": [250, 300],
+			"parameters": {
+				"path": "/webhook1"
+			}
+		},
+		{
+			"id": "2",
+			"name": "Timer Trigger",
+			"type": "n8n-nodes-base.scheduleTrigger",
+			"typeVersion": 1,
+			"position": [250, 450],
+			"parameters": {
+				"rule": {
+					"interval": [
+						{
+							"field": "hours",
+							"hoursInterval": 2
+						}
+					]
+				}
+			}
+		},
+		{
+			"id": "4",
+			"name": "Process Data",
+			"type": "n8n-nodes-base.code",
+			"typeVersion": 1,
+			"position": [650, 375],
+			"parameters": {
+				"jsCode": "return items;"
+			}
+		}
+	],
+	"connections": {
+		"HTTP Trigger": {
+			"main": [
+				[
+					{
+						"node": "Process Data",
+						"type": "main",
+						"index": 0
+					}
+				]
+			]
+		}
+	}
+}

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/example_workflows/simple_workflow.json

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+{
+	"name": "Simple Test Workflow",
+	"nodes": [
+		{
+			"id": "1",
+			"name": "Webhook Trigger",
+			"type": "n8n-nodes-base.webhook",
+			"typeVersion": 1,
+			"position": [250, 300],
+			"parameters": {
+				"path": "/test"
+			}
+		},
+		{
+			"id": "2",
+			"name": "Code",
+			"type": "n8n-nodes-base.code",
+			"typeVersion": 1,
+			"position": [450, 300],
+			"parameters": {
+				"jsCode": "return items;"
+			}
+		}
+	],
+	"connections": {
+		"Webhook Trigger": {
+			"main": [
+				[
+					{
+						"node": "Code",
+						"type": "main",
+						"index": 0
+					}
+				]
+			]
+		}
+	}
+}

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/justfile

@@ -0,0 +1,37 @@
+check:
+    just lint
+    just format-check
+    just typecheck
+
+run:
+    uv run python -m src.main
+
+sync:
+    uv sync --group dev
+
+sync-all:
+    uv sync --all-extras --group dev
+
+lint:
+    uv run ruff check
+
+lintfix:
+    uv run ruff check --fix
+
+format:
+    uv run ruff format
+
+format-check:
+    uv run ruff format --check
+
+test:
+    uv run pytest
+
+test-cov:
+    uv run pytest --cov=src --cov-report=term-missing
+
+test-v:
+    uv run pytest -vv
+
+typecheck:
+    uv run ty check src/

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/pyproject.toml

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+[project]
+name = "n8n-workflow-comparison"
+version = "0.1.0"
+description = "Graph-based workflow similarity comparison for n8n"
+requires-python = ">=3.11"
+dependencies = [
+    "networkx>=3.2",
+    "numpy>=2.3.4",
+    "pyyaml>=6.0",
+    "scipy>=1.16.3",
+]
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["."]
+
+[tool.pytest.ini_options]
+pythonpath = ["."]
+testpaths = ["tests"]
+addopts = "-v"
+
+[tool.coverage.run]
+source = ["."]
+omit = ["tests/*", "**/__pycache__/*"]
+
+
+[dependency-groups]
+dev = [
+    "pytest>=9.0.1",
+    "pytest-cov>=7.0.0",
+    "ruff>=0.14.5",
+    "ty>=0.0.1a26",
+]

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/src/__init__.py

@@ -0,0 +1,21 @@
+"""
+n8n Workflow Comparison Module
+
+Graph-based workflow similarity comparison using NetworkX.
+"""
+
+from __future__ import annotations
+
+from src.config_loader import WorkflowComparisonConfig, load_config
+from src.graph_builder import build_workflow_graph, graph_stats
+from src.similarity import calculate_graph_edit_distance
+
+__version__ = "0.1.0"
+
+__all__ = [
+    "WorkflowComparisonConfig",
+    "load_config",
+    "build_workflow_graph",
+    "graph_stats",
+    "calculate_graph_edit_distance",
+]

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/src/__main__.py

@@ -0,0 +1,8 @@
+"""
+Allow running as a module: python -m compare_workflows
+"""
+
+from compare_workflows import main
+
+if __name__ == "__main__":
+    main()

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/src/compare_workflows.py

@@ -0,0 +1,334 @@
+#!/usr/bin/env python3
+"""
+Workflow comparison using graph edit distance.
+
+Options:
+    --config PATH          Path to custom config file (.yaml or .json)
+    --preset NAME          Use built-in preset (strict|standard|lenient)
+    --output-format FORMAT Output format (json|summary) [default: json]
+    --verbose              Show detailed comparison info
+    --help                 Show this help message
+"""
+
+import argparse
+import json
+import sys
+from typing import Dict, Any
+
+from src.graph_builder import build_workflow_graph, graph_stats
+from src.similarity import calculate_graph_edit_distance
+from src.config_loader import load_config
+
+
+def parse_args():
+    """Parse command line arguments"""
+    parser = argparse.ArgumentParser(
+        description="Compare n8n workflows using graph edit distance",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog="""
+Examples:
+  # Use default configuration
+  python compare_workflows.py generated.json ground_truth.json
+
+  # Use a preset
+  python compare_workflows.py generated.json ground_truth.json --preset strict
+
+  # Use custom configuration
+  python compare_workflows.py generated.json ground_truth.json --config my-config.yaml
+
+  # Output summary instead of JSON
+  python compare_workflows.py generated.json ground_truth.json --output-format summary
+        """,
+    )
+
+    parser.add_argument("generated", help="Path to generated workflow JSON file")
+    parser.add_argument("ground_truth", help="Path to ground truth workflow JSON file")
+    parser.add_argument(
+        "--config", help="Path to custom configuration file (.yaml or .json)"
+    )
+    parser.add_argument(
+        "--preset",
+        choices=["strict", "standard", "lenient"],
+        help="Use built-in configuration preset",
+    )
+    parser.add_argument(
+        "--output-format",
+        choices=["json", "summary"],
+        default="json",
+        help="Output format (default: json)",
+    )
+    parser.add_argument(
+        "--verbose", action="store_true", help="Show detailed comparison information"
+    )
+
+    return parser.parse_args()
+
+
+def load_workflow(path: str) -> Dict[str, Any]:
+    """
+    Load workflow JSON from file.
+
+    Args:
+        path: Path to workflow JSON file
+
+    Returns:
+        Workflow dictionary
+
+    Raises:
+        SystemExit: If file cannot be loaded
+    """
+    try:
+        with open(path) as f:
+            return json.load(f)
+    except FileNotFoundError:
+        print(f"Error: Workflow file not found: {path}", file=sys.stderr)
+        sys.exit(1)
+    except json.JSONDecodeError as e:
+        print(f"Error: Invalid JSON in {path}: {e}", file=sys.stderr)
+        sys.exit(1)
+    except Exception as e:
+        print(f"Error loading {path}: {e}", file=sys.stderr)
+        sys.exit(1)
+
+
+def format_output_json(
+    result: Dict[str, Any], metadata: Dict[str, Any], verbose: bool = False
+) -> str:
+    """Format result as JSON"""
+    output: Dict[str, Any] = {
+        "similarity_score": result["similarity_score"],
+        "similarity_percentage": f"{result['similarity_score'] * 100:.1f}%",
+        "edit_cost": result["edit_cost"],
+        "max_possible_cost": result["max_possible_cost"],
+        "top_edits": result["top_edits"],
+        "metadata": metadata,
+    }
+
+    if verbose:
+        metadata_dict = output["metadata"]
+        assert isinstance(metadata_dict, dict)
+        metadata_dict["verbose"] = True
+    else:
+        for edit in output["top_edits"]:
+            if "parameter_diff" in edit:
+                del edit["parameter_diff"]
+
+    return json.dumps(output, indent=2)
+
+
+def _format_parameter_diff(
+    diff: Dict[str, Any],
+    indent: str = "",
+    max_value_length: int = 50,
+) -> list:
+    """
+    Format parameter diff for human-readable display.
+
+    Args:
+        diff: Parameter diff dictionary with 'added', 'removed', 'changed' keys
+        indent: Indentation prefix for each line
+        max_value_length: Maximum length for displayed values before truncation
+
+    Returns:
+        List of formatted lines
+    """
+    lines = []
+
+    def truncate_value(value: Any) -> str:
+        """Truncate long values for display"""
+        value_str = str(value)
+        if len(value_str) > max_value_length:
+            return value_str[:max_value_length] + "..."
+        return value_str
+
+    # Added parameters
+    if "added" in diff and diff["added"]:
+        lines.append(f"{indent}Added:")
+        for key, value in diff["added"].items():
+            lines.append(f"{indent}  + {key}: {truncate_value(value)}")
+
+    # Removed parameters
+    if "removed" in diff and diff["removed"]:
+        lines.append(f"{indent}Removed:")
+        for key, value in diff["removed"].items():
+            lines.append(f"{indent}  - {key}: {truncate_value(value)}")
+
+    # Changed parameters
+    if "changed" in diff and diff["changed"]:
+        lines.append(f"{indent}Changed:")
+        for key, value in diff["changed"].items():
+            if isinstance(value, dict) and "from" in value and "to" in value:
+                # Simple value change
+                lines.append(f"{indent}  ~ {key}:")
+                lines.append(f"{indent}      from: {truncate_value(value['from'])}")
+                lines.append(f"{indent}      to:   {truncate_value(value['to'])}")
+            elif isinstance(value, dict):
+                # Nested diff
+                lines.append(f"{indent}  ~ {key}:")
+                nested_lines = _format_parameter_diff(
+                    value, indent + "    ", max_value_length
+                )
+                lines.extend(nested_lines)
+
+    return lines
+
+
+def format_output_summary(
+    result: Dict[str, Any], metadata: Dict[str, Any], verbose: bool = False
+) -> str:
+    """Format result as human-readable summary"""
+    lines = []
+
+    # Header
+    lines.append("=" * 60)
+    lines.append("WORKFLOW COMPARISON SUMMARY")
+    lines.append("=" * 60)
+    lines.append("")
+
+    # Similarity score
+    similarity_pct = result["similarity_score"] * 100
+    lines.append(f"Overall Similarity: {similarity_pct:.1f}%")
+    lines.append(
+        f"Edit Cost:          {result['edit_cost']:.1f} / {result['max_possible_cost']:.1f}"
+    )
+    lines.append("")
+
+    # Configuration info
+    lines.append(f"Configuration: {metadata['config_name']}")
+    if metadata.get("config_description"):
+        lines.append(f"  {metadata['config_description']}")
+    lines.append("")
+
+    # Graph statistics
+    lines.append("Graph Statistics:")
+    lines.append(
+        f"  Generated workflow:    {metadata['generated_nodes']} nodes "
+        f"({metadata.get('generated_nodes_after_filter', metadata['generated_nodes'])} after filtering)"
+    )
+    lines.append(
+        f"  Ground truth workflow: {metadata['ground_truth_nodes']} nodes "
+        f"({metadata.get('ground_truth_nodes_after_filter', metadata['ground_truth_nodes'])} after filtering)"
+    )
+    lines.append("")
+
+    # Top edits
+    if result["top_edits"]:
+        lines.append(f"Top {len(result['top_edits'])} Required Edits:")
+        lines.append("-" * 60)
+
+        for i, edit in enumerate(result["top_edits"], 1):
+            priority = edit["priority"].upper()
+            cost = edit["cost"]
+            desc = edit["description"]
+
+            # Priority indicator
+            if priority == "CRITICAL":
+                indicator = "🔴"
+            elif priority == "MAJOR":
+                indicator = "🟠"
+            else:
+                indicator = "🟡"
+
+            lines.append(f"{i}. {indicator} [{priority}] Cost: {cost:.1f}")
+            lines.append(f"   {desc}")
+
+            # Add parameter diff if present
+            if verbose and "parameter_diff" in edit:
+                lines.append("")
+                lines.extend(
+                    _format_parameter_diff(edit["parameter_diff"], indent="   ")
+                )
+
+            lines.append("")
+    else:
+        lines.append("No edits required - workflows are identical!")
+        lines.append("")
+
+    # Pass/Fail indicator
+    lines.append("=" * 60)
+    if similarity_pct >= 70:
+        lines.append("✅ PASS - Workflows are sufficiently similar")
+    else:
+        lines.append("❌ FAIL - Workflows differ significantly")
+    lines.append("=" * 60)
+
+    return "\n".join(lines)
+
+
+def main():
+    """Main entry point"""
+    args = parse_args()
+
+    # Load workflows
+    generated = load_workflow(args.generated)
+    ground_truth = load_workflow(args.ground_truth)
+
+    # Load configuration
+    try:
+        if args.config:
+            config = load_config(args.config)
+        elif args.preset:
+            config = load_config(f"preset:{args.preset}")
+        else:
+            config = load_config()  # Default (standard)
+    except Exception as e:
+        print(f"Error loading configuration: {e}", file=sys.stderr)
+        sys.exit(1)
+
+    # Build graphs with config filtering
+    try:
+        g1 = build_workflow_graph(generated, config)
+        g2 = build_workflow_graph(ground_truth, config)
+    except Exception as e:
+        print(f"Error building workflow graphs: {e}", file=sys.stderr)
+        sys.exit(1)
+
+    # Get graph statistics
+    stats1 = graph_stats(g1)
+    stats2 = graph_stats(g2)
+
+    # Calculate similarity
+    try:
+        result = calculate_graph_edit_distance(g1, g2, config)
+    except Exception as e:
+        print(f"Error calculating similarity: {e}", file=sys.stderr)
+        sys.exit(1)
+
+    # Prepare metadata
+    metadata = {
+        "generated_nodes": len(generated.get("nodes", [])),
+        "ground_truth_nodes": len(ground_truth.get("nodes", [])),
+        "generated_nodes_after_filter": stats1["node_count"],
+        "ground_truth_nodes_after_filter": stats2["node_count"],
+        "config_name": config.name,
+        "config_description": config.description,
+    }
+
+    if args.verbose:
+        metadata["verbose_info"] = {
+            "generated_stats": stats1,
+            "ground_truth_stats": stats2,
+            "config_details": config.to_dict(),
+        }
+
+    # Format and output result
+    if args.output_format == "json":
+        output = format_output_json(result, metadata, args.verbose)
+        print(output)
+    elif args.output_format == "summary":
+        output = format_output_summary(result, metadata, args.verbose)
+        print(output)
+
+    # Always exit with 0 - let the caller interpret the similarity score
+    sys.exit(0)
+
+
+if __name__ == "__main__":
+    try:
+        main()
+    except KeyboardInterrupt:
+        print("\nInterrupted by user", file=sys.stderr)
+        sys.exit(130)
+    except Exception as e:
+        print(f"Unexpected error: {e}", file=sys.stderr)
+        sys.exit(1)

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/src/config_loader.py

@@ -0,0 +1,389 @@
+"""
+Configuration loader for workflow comparison.
+Supports loading from YAML, JSON, and built-in presets.
+"""
+
+from dataclasses import dataclass, field
+from typing import Dict, List, Optional, Any, Set
+from pathlib import Path
+import yaml
+import json
+import re
+
+
+def _get_param_path_matching_pattern(pattern: str) -> str:
+    """
+    Convert glob-like pattern to regex pattern.
+    Supports wildcards: ** (matches any chars including dots), * (matches any chars except dots)
+    """
+    # Use placeholders to preserve wildcards during escaping
+    regex_pattern = pattern.replace("**", "\x00DOUBLE_STAR\x00").replace(
+        "*", "\x00STAR\x00"
+    )
+    regex_pattern = regex_pattern.replace(".", r"\.")
+    regex_pattern = regex_pattern.replace("\x00DOUBLE_STAR\x00", ".*").replace(
+        "\x00STAR\x00", "[^.]*"
+    )
+    return regex_pattern
+
+
+@dataclass
+class NodeIgnoreRule:
+    """Rule for ignoring nodes during comparison"""
+
+    pattern: Optional[str] = None
+    name: Optional[str] = None
+    node_type: Optional[str] = None
+    reason: str = ""
+
+    def matches(self, node: Dict) -> bool:
+        """Check if this rule matches a node"""
+        if self.name and node.get("name") == self.name:
+            return True
+        if self.pattern and re.match(self.pattern, node.get("name", "")):
+            return True
+        if self.node_type and node.get("type") == self.node_type:
+            return True
+        return False
+
+
+@dataclass
+class ParameterComparisonRule:
+    """Rule for comparing specific parameters"""
+
+    parameter: str
+    type: str  # 'semantic', 'normalized', 'exact', 'numeric'
+    threshold: Optional[float] = None
+    tolerance: Optional[float] = None
+    cost_if_below: float = 0.0
+    cost_if_exceeded: float = 0.0
+    options: Dict[str, Any] = field(default_factory=dict)
+
+    def matches_parameter(self, param_path: str) -> bool:
+        """Check if this rule applies to a parameter path"""
+        regex_pattern = _get_param_path_matching_pattern(self.parameter)
+        return bool(re.match(f"^{regex_pattern}$", param_path))
+
+
+@dataclass
+class ExemptionRule:
+    """Rule for exempting certain nodes from full cost"""
+
+    name_pattern: Optional[str] = None
+    node_type: Optional[str] = None
+    penalty: float = 0.0
+    reason: str = ""
+    when: Optional[Dict[str, Any]] = None
+
+    def matches(self, node: Dict) -> bool:
+        """Check if node matches exemption"""
+        match = False
+        if self.name_pattern and re.match(self.name_pattern, node.get("name", "")):
+            match = True
+        if self.node_type and node.get("type") == self.node_type:
+            match = True
+
+        # Check additional conditions
+        if match and self.when:
+            for key, value in self.when.items():
+                if node.get(key) != value:
+                    return False
+
+        return match
+
+
+@dataclass
+class WorkflowComparisonConfig:
+    """Complete configuration for workflow comparison"""
+
+    version: str = "1.0"
+    name: str = "default"
+    description: str = ""
+
+    # Cost weights
+    node_insertion_cost: float = 10.0
+    node_deletion_cost: float = 10.0
+    node_substitution_same_type: float = 1.0
+    node_substitution_similar_type: float = 5.0
+    node_substitution_different_type: float = 15.0
+    node_substitution_trigger: float = 50.0
+
+    edge_insertion_cost: float = 5.0
+    edge_deletion_cost: float = 5.0
+    edge_substitution_cost: float = 3.0
+
+    parameter_mismatch_weight: float = 0.5
+    parameter_nested_weight: float = 0.3
+
+    # Similarity groups
+    similarity_groups: Dict[str, List[str]] = field(default_factory=dict)
+
+    # Ignore rules
+    ignored_node_rules: List[NodeIgnoreRule] = field(default_factory=list)
+    ignored_node_types: Set[str] = field(default_factory=set)
+    ignored_global_parameters: Set[str] = field(default_factory=set)
+    ignored_node_type_parameters: Dict[str, Set[str]] = field(default_factory=dict)
+    ignored_parameter_paths: List[str] = field(default_factory=list)
+
+    # Parameter comparison rules
+    parameter_rules: List[ParameterComparisonRule] = field(default_factory=list)
+
+    # Exemptions
+    optional_in_generated: List[ExemptionRule] = field(default_factory=list)
+    optional_in_ground_truth: List[ExemptionRule] = field(default_factory=list)
+
+    # Connection rules
+    ignored_connection_types: Set[str] = field(default_factory=set)
+    equivalent_connection_types: List[List[str]] = field(default_factory=list)
+
+    # Output config
+    max_edits: int = 15
+    group_by: str = "priority"
+    include_explanations: bool = True
+    include_suggestions: bool = True
+
+    def should_ignore_node(self, node: Dict) -> bool:
+        """Check if node should be ignored"""
+        # Check node type
+        if node.get("type") in self.ignored_node_types:
+            return True
+
+        # Check node rules
+        for rule in self.ignored_node_rules:
+            if rule.matches(node):
+                return True
+
+        return False
+
+    def should_ignore_parameter(self, node_type: str, param_path: str) -> bool:
+        """Check if parameter should be ignored"""
+        # Global parameters
+        param_name = param_path.split(".")[-1]
+        if param_name in self.ignored_global_parameters:
+            return True
+
+        # Node type specific
+        if node_type in self.ignored_node_type_parameters:
+            if param_path in self.ignored_node_type_parameters[node_type]:
+                return True
+            # Check wildcards
+            for ignored_path in self.ignored_node_type_parameters[node_type]:
+                if self._matches_path_pattern(param_path, ignored_path):
+                    return True
+
+        # Parameter path patterns
+        for pattern in self.ignored_parameter_paths:
+            if self._matches_path_pattern(param_path, pattern):
+                return True
+
+        return False
+
+    def get_parameter_rule(self, param_path: str) -> Optional[ParameterComparisonRule]:
+        """Get comparison rule for parameter"""
+        for rule in self.parameter_rules:
+            if rule.matches_parameter(param_path):
+                return rule
+        return None
+
+    def get_exemption_penalty(
+        self,
+        node: Dict,
+        context: str,  # 'generated' or 'ground_truth'
+    ) -> Optional[float]:
+        """Get exemption penalty for a node, if applicable"""
+        exemptions = (
+            self.optional_in_generated
+            if context == "generated"
+            else self.optional_in_ground_truth
+        )
+
+        for exemption in exemptions:
+            if exemption.matches(node):
+                return exemption.penalty
+
+        return None
+
+    @staticmethod
+    def _matches_path_pattern(path: str, pattern: str) -> bool:
+        """Check if path matches pattern (supports ** and *)"""
+        regex_pattern = _get_param_path_matching_pattern(pattern)
+        return bool(re.match(f"^{regex_pattern}$", path))
+
+    def are_node_types_similar(self, type1: str, type2: str) -> bool:
+        """Check if two node types are in the same similarity group"""
+        for group_name, types in self.similarity_groups.items():
+            if type1 in types and type2 in types:
+                return True
+        return False
+
+    def to_dict(self) -> Dict:
+        """Convert config to dictionary for serialization"""
+        return {
+            "version": self.version,
+            "name": self.name,
+            "description": self.description,
+            "costs": {
+                "nodes": {
+                    "insertion": self.node_insertion_cost,
+                    "deletion": self.node_deletion_cost,
+                    "substitution": {
+                        "same_type": self.node_substitution_same_type,
+                        "similar_type": self.node_substitution_similar_type,
+                        "different_type": self.node_substitution_different_type,
+                        "trigger_mismatch": self.node_substitution_trigger,
+                    },
+                },
+                "edges": {
+                    "insertion": self.edge_insertion_cost,
+                    "deletion": self.edge_deletion_cost,
+                    "substitution": self.edge_substitution_cost,
+                },
+                "parameters": {
+                    "mismatch_weight": self.parameter_mismatch_weight,
+                    "nested_weight": self.parameter_nested_weight,
+                },
+            },
+            "similarity_groups": self.similarity_groups,
+            "max_edits": self.max_edits,
+        }
+
+    @classmethod
+    def from_yaml(cls, path: Path) -> "WorkflowComparisonConfig":
+        """Load configuration from YAML file"""
+        with open(path) as f:
+            data = yaml.safe_load(f)
+        return cls._from_dict(data)
+
+    @classmethod
+    def from_json(cls, path: Path) -> "WorkflowComparisonConfig":
+        """Load configuration from JSON file"""
+        with open(path) as f:
+            data = json.load(f)
+        return cls._from_dict(data)
+
+    @classmethod
+    def _from_dict(cls, data: Dict) -> "WorkflowComparisonConfig":
+        """Parse configuration dictionary"""
+        config = cls()
+
+        # Basic info
+        config.version = data.get("version", "1.0")
+        config.name = data.get("name", "default")
+        config.description = data.get("description", "")
+
+        # Costs
+        costs = data.get("costs", {})
+        nodes = costs.get("nodes", {})
+        config.node_insertion_cost = nodes.get("insertion", 10.0)
+        config.node_deletion_cost = nodes.get("deletion", 10.0)
+
+        subst = nodes.get("substitution", {})
+        config.node_substitution_same_type = subst.get("same_type", 1.0)
+        config.node_substitution_similar_type = subst.get("similar_type", 5.0)
+        config.node_substitution_different_type = subst.get("different_type", 15.0)
+        config.node_substitution_trigger = subst.get("trigger_mismatch", 50.0)
+
+        edges = costs.get("edges", {})
+        config.edge_insertion_cost = edges.get("insertion", 5.0)
+        config.edge_deletion_cost = edges.get("deletion", 5.0)
+        config.edge_substitution_cost = edges.get("substitution", 3.0)
+
+        params = costs.get("parameters", {})
+        config.parameter_mismatch_weight = params.get("mismatch_weight", 0.5)
+        config.parameter_nested_weight = params.get("nested_weight", 0.3)
+
+        # Similarity groups
+        config.similarity_groups = data.get("similarity_groups", {})
+
+        # Ignore rules
+        ignore = data.get("ignore", {})
+
+        # Node ignore rules
+        for node_rule in ignore.get("nodes", []):
+            config.ignored_node_rules.append(NodeIgnoreRule(**node_rule))
+
+        config.ignored_node_types = set(ignore.get("node_types", []))
+        config.ignored_global_parameters = set(ignore.get("global_parameters", []))
+
+        # Node type parameters
+        for node_type, params in ignore.get("node_type_parameters", {}).items():
+            config.ignored_node_type_parameters[node_type] = set(params)
+
+        config.ignored_parameter_paths = ignore.get("parameter_paths", [])
+
+        # Parameter comparison rules
+        param_comp = data.get("parameter_comparison", {})
+        for rule_data in param_comp.get("fuzzy_match", []):
+            config.parameter_rules.append(ParameterComparisonRule(**rule_data))
+
+        for rule_data in param_comp.get("numeric_tolerance", []):
+            rule_data["type"] = "numeric"
+            config.parameter_rules.append(ParameterComparisonRule(**rule_data))
+
+        # Exemptions
+        exemptions = data.get("exemptions", {})
+        for exemption_data in exemptions.get("optional_in_generated", []):
+            config.optional_in_generated.append(ExemptionRule(**exemption_data))
+
+        for exemption_data in exemptions.get("optional_in_ground_truth", []):
+            config.optional_in_ground_truth.append(ExemptionRule(**exemption_data))
+
+        # Connection rules
+        connections = data.get("connections", {})
+        config.ignored_connection_types = set(
+            connections.get("ignore_connection_types", [])
+        )
+        config.equivalent_connection_types = connections.get("equivalent_types", [])
+
+        # Output config
+        output = data.get("output", {})
+        config.max_edits = output.get("max_edits", 15)
+        config.group_by = output.get("group_by", "priority")
+        config.include_explanations = output.get("include_explanations", True)
+        config.include_suggestions = output.get("include_suggestions", True)
+
+        return config
+
+    @classmethod
+    def load_preset(cls, preset_name: str) -> "WorkflowComparisonConfig":
+        """Load a built-in preset configuration"""
+        presets_dir = Path(__file__).parent / "configs" / "presets"
+        preset_path = presets_dir / f"{preset_name}.yaml"
+
+        if not preset_path.exists():
+            raise ValueError(f"Preset '{preset_name}' not found at {preset_path}")
+
+        return cls.from_yaml(preset_path)
+
+
+def load_config(config_source: Optional[str] = None) -> WorkflowComparisonConfig:
+    """
+    Load configuration from various sources.
+
+    Args:
+        config_source: Can be:
+            - None: use default config
+            - "preset:name": load built-in preset (e.g., "preset:strict")
+            - "/path/to/config.yaml": load custom YAML file
+            - "/path/to/config.json": load custom JSON file
+
+    Returns:
+        WorkflowComparisonConfig instance
+    """
+    if not config_source:
+        return WorkflowComparisonConfig()
+
+    if config_source.startswith("preset:"):
+        preset_name = config_source.split(":", 1)[1]
+        return WorkflowComparisonConfig.load_preset(preset_name)
+
+    path = Path(config_source)
+    if not path.exists():
+        raise ValueError(f"Config file not found: {config_source}")
+
+    if path.suffix in [".yaml", ".yml"]:
+        return WorkflowComparisonConfig.from_yaml(path)
+    elif path.suffix == ".json":
+        return WorkflowComparisonConfig.from_json(path)
+    else:
+        raise ValueError(f"Unsupported config format: {path.suffix}")

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/src/configs/presets/lenient.yaml

@@ -0,0 +1,83 @@
+version: "1.0"
+name: "lenient"
+description: "Lenient comparison - focus on structure over details"
+
+# Cost weights - lower penalties
+costs:
+  nodes:
+    insertion: 7.0
+    deletion: 7.0
+    substitution:
+      same_type: 0.1  # Very low cost for parameter differences
+      similar_type: 2.0
+      different_type: 8.0
+      trigger_mismatch: 50.0
+
+  edges:
+    insertion: 3.0
+    deletion: 3.0
+    substitution: 2.0
+
+  parameters:
+    mismatch_weight: 0.3
+    nested_weight: 0.1
+
+# Node type similarity groups (same as standard)
+similarity_groups:
+  ai_llms:
+    - "@n8n/n8n-nodes-langchain.lmChatOpenAi"
+    - "@n8n/n8n-nodes-langchain.lmChatAnthropic"
+    - "@n8n/n8n-nodes-langchain.lmChatOllama"
+    - "@n8n/n8n-nodes-langchain.lmChatMistralCloud"
+    - "@n8n/n8n-nodes-langchain.lmChatAws"
+    - "@n8n/n8n-nodes-langchain.lmChatGroq"
+
+
+ignore:
+  node_types:
+    - "n8n-nodes-base.stickyNote"
+    - "n8n-nodes-base.noOp"
+
+  global_parameters:
+    - "position"
+    - "name"
+    - "id"
+    - "notes"
+    - "notesInFlow"
+    - "color"
+    - "alwaysOutputData"
+    - "executeOnce"
+
+  # Ignore implementation details for specific node types
+  node_type_parameters:
+    "@n8n/n8n-nodes-langchain.agent":
+      - "options.*"  # Ignore all options
+
+    "@n8n/n8n-nodes-langchain.lmChatOpenAi":
+      - "model"  # Model choice is flexible
+
+    "@n8n/n8n-nodes-langchain.lmChatAnthropic":
+      - "model"
+
+  # Ignore credential references (might differ between environments)
+  parameter_paths:
+    - "**.credentials"
+
+# Parameter comparison - very tolerant
+parameter_comparison:
+  # High tolerance for numeric values
+  numeric_tolerance:
+    - parameter: "options.temperature"
+      tolerance: 0.3
+      cost_if_exceeded: 0.5
+
+    - parameter: "options.maxTokens"
+      tolerance: 500
+      cost_if_exceeded: 0.5
+
+# Output configuration
+output:
+  max_edits: 20
+  group_by: "priority"
+  include_explanations: true
+  include_suggestions: true

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/src/configs/presets/standard.yaml

@@ -0,0 +1,60 @@
+version: "1.0"
+name: "standard"
+description: "Standard balanced comparison configuration"
+
+# Cost weights - balanced approach
+costs:
+  nodes:
+    insertion: 10.0
+    deletion: 10.0
+    substitution:
+      same_type: 1.0
+      similar_type: 5.0
+      different_type: 15.0
+      trigger_mismatch: 50.0
+
+  edges:
+    insertion: 2.0
+    deletion: 2.0
+    substitution: 1.0
+
+  parameters:
+    mismatch_weight: 0.5
+    nested_weight: 0.3
+
+# Ignore rules
+ignore:
+  # Ignore UI-only nodes
+  node_types:
+    - "n8n-nodes-base.stickyNote"
+
+  # Ignore cosmetic parameters
+  global_parameters:
+    - "position"
+    - "id"
+    - "notes"
+    - "notesInFlow"
+    - "color"
+
+
+# Ignore credential references (might differ between environments)
+parameter_paths:
+  - "**.credentials"
+
+# Parameter comparison rules
+parameter_comparison:
+  # Numeric tolerance for temperature and similar params
+  numeric_tolerance:
+    - parameter: "options.temperature"
+      tolerance: 0.1
+      cost_if_exceeded: 2.0
+
+    - parameter: "options.maxTokens"
+      tolerance: 100
+      cost_if_exceeded: 1.0
+
+# Output configuration
+output:
+  max_edits: 29
+  group_by: "priority"
+  include_explanations: true

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/src/configs/presets/strict.yaml

@@ -0,0 +1,44 @@
+version: "1.0"
+name: "strict"
+description: "Strict comparison - exact match required for most aspects"
+
+# Cost weights - higher penalties
+costs:
+  nodes:
+    insertion: 15.0
+    deletion: 15.0
+    substitution:
+      same_type: 0.5  # Very sensitive to parameter changes
+      similar_type: 10.0
+      different_type: 25.0
+      trigger_mismatch: 100.0  # Trigger mismatch is critical
+
+  edges:
+    insertion: 8.0
+    deletion: 8.0
+    substitution: 5.0
+
+  parameters:
+    mismatch_weight: 1.0  # High weight for parameter differences
+    nested_weight: 0.8
+
+# Minimal ignores - most things should match
+ignore:
+  # Only ignore pure UI elements
+  node_types:
+    - "n8n-nodes-base.stickyNote"
+
+  # Only ignore metadata that doesn't affect execution
+  global_parameters:
+    - "position"
+    - "id"
+
+# No parameter tolerance - exact match required
+parameter_comparison: {}
+
+# Output configuration
+output:
+  max_edits: 20  # Show more edits for strict mode
+  group_by: "priority"
+  include_explanations: true
+  include_suggestions: true

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/src/cost_functions.py

@@ -0,0 +1,497 @@
+"""
+Cost functions for graph edit distance operations.
+Configuration-aware costs for node and edge operations.
+"""
+
+import re
+from typing import Dict, Any
+from src.config_loader import WorkflowComparisonConfig, ParameterComparisonRule
+
+
+def normalize_expression(value: Any) -> Any:
+    """
+    Normalize expression strings for comparison.
+
+    This function:
+    1. Removes all /* */ style comments
+    2. Normalizes whitespace
+    3. Normalizes $fromAI function calls with optional parameters
+
+    Args:
+        value: The value to normalize (typically a string expression)
+
+    Returns:
+        Normalized value for comparison
+    """
+    if not isinstance(value, str):
+        return value
+
+    # Remove all /* */ style comments
+    cleaned = re.sub(r"/\*.*?\*/", "", value)
+
+    # Normalize whitespace - collapse multiple spaces/tabs to single space
+    cleaned = re.sub(r"\s+", " ", cleaned)
+
+    # Normalize $fromAI calls with optional parameters
+    def normalize_fromAI(match):
+        # Extract the first parameter and clean it up
+        first_param = match.group(1).strip()
+        # If there's a comma in first_param, split and take first part
+        if "," in first_param:
+            first_param = first_param.split(",")[0].strip()
+        return f"$fromAI({first_param})"
+
+    cleaned = re.sub(
+        r"\$fromAI\(([^)]*?)\)",
+        normalize_fromAI,
+        cleaned,
+    )
+
+    # Strip any remaining extra whitespace
+    cleaned = cleaned.strip()
+
+    return cleaned
+
+
+def node_substitution_cost(
+    node1_data: Dict[str, Any],
+    node2_data: Dict[str, Any],
+    config: WorkflowComparisonConfig,
+) -> float:
+    """
+    Calculate cost of substituting node1 with node2.
+
+    Args:
+        node1_data: Attributes of first node
+        node2_data: Attributes of second node
+        config: Configuration with cost weights
+
+    Returns:
+        Cost value (0 = identical, higher = more different)
+    """
+    # Check for exemptions
+    original_data = node1_data.get("parameters", "{}")
+    exemption_penalty = config.get_exemption_penalty(original_data, "generated")
+    if exemption_penalty is not None:
+        return exemption_penalty
+
+    # Get node types first for trigger detection
+    type1 = node1_data.get("type", "")
+    type2 = node2_data.get("type", "")
+
+    # Critical: Trigger nodes
+    is_trigger1 = node1_data.get("is_trigger", False)
+    is_trigger2 = node2_data.get("is_trigger", False)
+
+    # If both are triggers but different types, high cost
+    if is_trigger1 and is_trigger2 and type1 != type2:
+        return config.node_substitution_trigger
+
+    # If one is trigger and other isn't, high cost
+    if is_trigger1 != is_trigger2:
+        return config.node_substitution_trigger
+
+    # Same type: compare parameters
+
+    if type1 == type2:
+        # Get parameters directly from node data
+        params1 = node1_data.get("parameters", {})
+        params2 = node2_data.get("parameters", {})
+
+        param_diff = compare_parameters(params1, params2, type1, config)
+
+        # Check if names match using the hash
+        # This prevents GED from swapping nodes with same type but different names
+        name_hash1 = node1_data.get("_name_hash", 0)
+        name_hash2 = node2_data.get("_name_hash", 0)
+
+        # If hashes are present and different, add penalty
+        # This prevents swapping "Slack Assistant" with "Master Orchestrator Agent"
+        # Names are normalized (smart quotes -> regular quotes) before hashing
+        name_mismatch_penalty = 0.0
+        if name_hash1 != 0 and name_hash2 != 0 and name_hash1 != name_hash2:
+            name_mismatch_penalty = config.node_substitution_different_type * 0.5
+
+        # If parameters are identical and names match, no cost
+        if param_diff == 0 and name_mismatch_penalty == 0:
+            return 0.0
+
+        # Otherwise, base cost plus parameter difference plus name penalty
+        return (
+            config.node_substitution_same_type
+            + (param_diff * config.parameter_mismatch_weight)
+            + name_mismatch_penalty
+        )
+
+    # Similar types (from config)
+    if config.are_node_types_similar(type1, type2):
+        return config.node_substitution_similar_type
+
+    # Completely different
+    return config.node_substitution_different_type
+
+
+def node_deletion_cost(
+    node_data: Dict[str, Any], config: WorkflowComparisonConfig
+) -> float:
+    """
+    Calculate cost of deleting a node.
+
+    Args:
+        node_data: Attributes of the node to delete
+        config: Configuration with cost weights
+
+    Returns:
+        Cost value
+    """
+    # Check for exemptions
+    original_data = node_data.get("parameters", "{}")
+    exemption_penalty = config.get_exemption_penalty(original_data, "generated")
+    if exemption_penalty is not None:
+        return exemption_penalty
+
+    is_trigger = node_data.get("is_trigger", False)
+    if is_trigger:
+        return config.node_substitution_trigger / 2
+
+    return config.node_deletion_cost
+
+
+def node_insertion_cost(
+    node_data: Dict[str, Any], config: WorkflowComparisonConfig
+) -> float:
+    """
+    Calculate cost of inserting a node.
+
+    Args:
+        node_data: Attributes of the node to insert
+        config: Configuration with cost weights
+
+    Returns:
+        Cost value
+    """
+    # Check for exemptions
+    original_data = node_data.get("parameters", "{}")
+    exemption_penalty = config.get_exemption_penalty(original_data, "ground_truth")
+    if exemption_penalty is not None:
+        return exemption_penalty
+    is_trigger = node_data.get("is_trigger", False)
+    if is_trigger:
+        return config.node_substitution_trigger / 2
+
+    return config.node_insertion_cost
+
+
+def edge_substitution_cost(
+    edge1_data: Dict[str, Any],
+    edge2_data: Dict[str, Any],
+    config: WorkflowComparisonConfig,
+) -> float:
+    """
+    Calculate cost of changing edge connection type.
+
+    Args:
+        edge1_data: Attributes of first edge
+        edge2_data: Attributes of second edge
+        config: Configuration with cost weights
+
+    Returns:
+        Cost value
+    """
+    # Check if source and target node types match
+    # If they do, this edge is likely following a node match
+    source_type1 = edge1_data.get("source_node_type", "")
+    source_type2 = edge2_data.get("source_node_type", "")
+    target_type1 = edge1_data.get("target_node_type", "")
+    target_type2 = edge2_data.get("target_node_type", "")
+
+    # If both source and target node types match, check connection compatibility
+    if source_type1 == source_type2 and target_type1 == target_type2:
+        conn_type1 = edge1_data.get("connection_type", "main")
+        conn_type2 = edge2_data.get("connection_type", "main")
+
+        # No cost if connection types are identical
+        if conn_type1 == conn_type2:
+            return 0.0
+
+        # Check for equivalent types in config
+        for equiv_group in config.equivalent_connection_types:
+            if conn_type1 in equiv_group and conn_type2 in equiv_group:
+                return 0.0  # No cost for equivalent types
+
+        # If node types match but connection types differ significantly,
+        # this is still an edge substitution with cost
+        return config.edge_substitution_cost
+
+    # Node types don't match - this is a structural change
+    # Higher cost because the edge endpoints are different
+    return config.edge_substitution_cost
+
+
+def edge_deletion_cost(
+    edge_data: Dict[str, Any], config: WorkflowComparisonConfig
+) -> float:
+    """Calculate cost of deleting an edge"""
+    return config.edge_deletion_cost
+
+
+def edge_insertion_cost(
+    edge_data: Dict[str, Any], config: WorkflowComparisonConfig
+) -> float:
+    """Calculate cost of inserting an edge"""
+    return config.edge_insertion_cost
+
+
+def compare_parameters(
+    params1: Dict[str, Any],
+    params2: Dict[str, Any],
+    node_type: str,
+    config: WorkflowComparisonConfig,
+    path_prefix: str = "",
+) -> float:
+    """
+    Deep comparison of parameters with config-aware filtering.
+
+    Args:
+        params1: First parameter dictionary
+        params2: Second parameter dictionary
+        node_type: Type of the node (for node-specific rules)
+        config: Configuration with comparison rules
+        path_prefix: Current parameter path (for nested params)
+
+    Returns:
+        Score representing parameter difference (higher = more different)
+    """
+    all_keys = set(params1.keys()) | set(params2.keys())
+    diff_score = 0.0
+
+    for key in all_keys:
+        param_path = f"{path_prefix}.{key}" if path_prefix else key
+
+        # Check if this parameter should be ignored (should be filtered already, but double-check)
+        if config.should_ignore_parameter(node_type, param_path):
+            continue
+
+        # Get comparison rule for this parameter
+        rule = config.get_parameter_rule(param_path)
+
+        # Handle missing keys
+        if key not in params1 or key not in params2:
+            diff_score += 1.0
+            continue
+
+        val1, val2 = params1[key], params2[key]
+
+        # Normalize expressions for comparison
+        val1_cleaned = normalize_expression(val1)
+        val2_cleaned = normalize_expression(val2)
+
+        # Apply comparison rule if exists
+        if rule:
+            cost = apply_comparison_rule(val1_cleaned, val2_cleaned, rule)
+            diff_score += cost
+            continue
+
+        # Default comparison logic
+        if isinstance(val1_cleaned, dict) and isinstance(val2_cleaned, dict):
+            # Recursive for nested objects
+            nested_diff = compare_parameters(
+                val1_cleaned, val2_cleaned, node_type, config, param_path
+            )
+            diff_score += nested_diff * config.parameter_nested_weight
+        elif isinstance(val1_cleaned, list) and isinstance(val2_cleaned, list):
+            # Compare lists (order matters)
+            diff_score += compare_lists(val1_cleaned, val2_cleaned, config)
+        elif val1_cleaned != val2_cleaned:
+            diff_score += 1.0
+
+    return diff_score
+
+
+def compare_lists(list1: list, list2: list, config: WorkflowComparisonConfig) -> float:
+    """
+    Compare two lists with tolerance for order and content.
+
+    Args:
+        list1: First list
+        list2: Second list
+        config: Configuration
+
+    Returns:
+        Difference score
+    """
+    # Simple approach: penalize length difference and content difference
+    if len(list1) != len(list2):
+        return abs(len(list1) - len(list2)) * 0.5
+
+    # Compare elements pairwise
+    diff = 0.0
+    for v1, v2 in zip(list1, list2):
+        if isinstance(v1, dict) and isinstance(v2, dict):
+            # Nested dict comparison (simplified)
+            if v1 != v2:
+                diff += 0.5
+        elif v1 != v2:
+            diff += 1.0
+
+    return diff
+
+
+def apply_comparison_rule(val1: Any, val2: Any, rule: ParameterComparisonRule) -> float:
+    """
+    Apply custom comparison rule to parameter values.
+
+    Args:
+        val1: First value
+        val2: Second value
+        rule: Comparison rule to apply
+
+    Returns:
+        Cost based on rule
+    """
+    if rule.type == "semantic":
+        # Semantic similarity (simplified version)
+        similarity = calculate_semantic_similarity(str(val1), str(val2))
+        if similarity >= (rule.threshold or 0.8):
+            return 0.0
+        return rule.cost_if_below
+
+    elif rule.type == "numeric":
+        # Numeric tolerance
+        try:
+            num1, num2 = float(val1), float(val2)
+            if abs(num1 - num2) <= (rule.tolerance or 0):
+                return 0.0
+            return rule.cost_if_exceeded
+        except (ValueError, TypeError):
+            # Not numeric, count as different
+            return rule.cost_if_exceeded
+
+    elif rule.type == "normalized":
+        # Normalized comparison (e.g., URLs)
+        norm1 = normalize_value(val1, rule.options)
+        norm2 = normalize_value(val2, rule.options)
+        if norm1 == norm2:
+            return 0.0
+        return 1.0
+
+    # Default: exact match
+    return 0.0 if val1 == val2 else 1.0
+
+
+def calculate_semantic_similarity(text1: str, text2: str) -> float:
+    """
+    Calculate semantic similarity between two text strings.
+
+    This is a placeholder using simple word overlap (Jaccard similarity).
+    In a production system, this could use sentence-transformers or similar.
+
+    Args:
+        text1: First text
+        text2: Second text
+
+    Returns:
+        Similarity score 0-1 (1 = identical)
+    """
+    # Convert to lowercase and split into words
+    words1 = set(text1.lower().split())
+    words2 = set(text2.lower().split())
+
+    if not words1 and not words2:
+        return 1.0
+    if not words1 or not words2:
+        return 0.0
+
+    # Jaccard similarity: intersection / union
+    intersection = words1 & words2
+    union = words1 | words2
+
+    return len(intersection) / len(union)
+
+
+def normalize_value(value: Any, options: Dict[str, Any]) -> Any:
+    """
+    Normalize value based on options.
+
+    Args:
+        value: Value to normalize
+        options: Normalization options [ignore_trailing_slash, case_insensitive]
+
+    Returns:
+        Normalized value
+    """
+    if isinstance(value, str):
+        # URL normalization
+        if value.startswith("http"):
+            normalized = value
+            if options.get("ignore_trailing_slash", False):
+                normalized = normalized.rstrip("/")
+            # Could add more URL normalization here
+            return normalized
+
+        # String normalization
+        if options.get("case_insensitive", False):
+            return value.lower()
+
+    return value
+
+
+def get_parameter_diff(
+    params1: Dict[str, Any],
+    params2: Dict[str, Any],
+    node_type: str,
+    config: WorkflowComparisonConfig,
+    path_prefix: str = "",
+) -> Dict[str, Any]:
+    """
+    Get detailed diff of parameters for display purposes.
+
+    Args:
+        params1: First parameter dictionary
+        params2: Second parameter dictionary
+        node_type: Type of the node (for node-specific rules)
+        config: Configuration with comparison rules
+        path_prefix: Current parameter path (for nested params)
+
+    Returns:
+        Dictionary with added, removed, and changed parameters
+    """
+    diff = {"added": {}, "removed": {}, "changed": {}}
+
+    all_keys = set(params1.keys()) | set(params2.keys())
+
+    for key in all_keys:
+        param_path = f"{path_prefix}.{key}" if path_prefix else key
+
+        # Skip ignored parameters
+        if config.should_ignore_parameter(node_type, param_path):
+            continue
+
+        if key not in params1:
+            # Parameter added in params2
+            diff["added"][key] = params2[key]
+        elif key not in params2:
+            # Parameter removed in params1
+            diff["removed"][key] = params1[key]
+        else:
+            val1, val2 = params1[key], params2[key]
+
+            # Normalize expressions before comparing
+            val1_cleaned = normalize_expression(val1)
+            val2_cleaned = normalize_expression(val2)
+
+            # Handle nested dicts
+            if isinstance(val1_cleaned, dict) and isinstance(val2_cleaned, dict):
+                nested_diff = get_parameter_diff(
+                    val1_cleaned, val2_cleaned, node_type, config, param_path
+                )
+                if any(nested_diff.values()):
+                    diff["changed"][key] = nested_diff
+            elif val1_cleaned != val2_cleaned:
+                # Store cleaned values for display
+                diff["changed"][key] = {"from": val1_cleaned, "to": val2_cleaned}
+
+    # Clean up empty sections
+    diff = {k: v for k, v in diff.items() if v}
+
+    return diff

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/src/graph_builder.py

@@ -0,0 +1,222 @@
+"""
+Build NetworkX graphs from n8n workflow JSON structures.
+"""
+
+import networkx as nx
+from typing import Dict, Any, Optional
+from src.config_loader import WorkflowComparisonConfig
+
+
+def build_workflow_graph(
+    workflow: Dict[str, Any], config: Optional[WorkflowComparisonConfig] = None
+) -> nx.DiGraph:
+    """
+    Convert n8n workflow to NetworkX directed graph.
+
+    Args:
+        workflow: n8n workflow JSON (with 'nodes' and 'connections')
+        config: Optional configuration for filtering
+
+    Returns:
+        NetworkX DiGraph with nodes and edges
+    """
+    G = nx.DiGraph()
+
+    if config is None:
+        config = WorkflowComparisonConfig()
+
+    # Add nodes with attributes
+    for node in workflow.get("nodes", []):
+        # Check if node should be ignored
+        if config.should_ignore_node(node):
+            continue
+
+        node_name = node.get("name", node.get("id", "unknown"))
+
+        # Filter parameters based on config
+        filtered_params = _filter_parameters(
+            node.get("parameters", {}), node.get("type", ""), config
+        )
+
+        # Add node with filtered parameters
+        G.add_node(
+            node_name,
+            type=node.get("type", ""),
+            type_version=node.get("typeVersion", 1),
+            parameters=filtered_params,
+            is_trigger=_is_trigger_node(node),
+        )
+
+    # Add edges from connections
+    connections = workflow.get("connections", {})
+    for source_name, source_conns in connections.items():
+        # Skip if source node was filtered out
+        if source_name not in G:
+            continue
+
+        for conn_type, conn_arrays in source_conns.items():
+            # Check if this connection type should be ignored
+            if conn_type in config.ignored_connection_types:
+                continue
+
+            # conn_arrays is typically: [[connections], [connections], ...]
+            # where first index is output index
+            for output_index, conn_array in enumerate(conn_arrays):
+                if conn_array is None:
+                    continue
+
+                for conn in conn_array:
+                    target_name = conn.get("node")
+
+                    # Skip if target node was filtered out
+                    if target_name not in G:
+                        continue
+
+                    # Add edge with connection metadata
+                    # Include source and target node info for better matching
+                    source_node_data = G.nodes[source_name]
+                    target_node_data = G.nodes[target_name]
+
+                    G.add_edge(
+                        source_name,
+                        target_name,
+                        connection_type=conn.get("type", "main"),
+                        source_index=output_index,
+                        target_index=conn.get("index", 0),
+                        source_node_type=source_node_data.get("type", ""),
+                        target_node_type=target_node_data.get("type", ""),
+                    )
+
+    return G
+
+
+def _filter_parameters(
+    params: Dict[str, Any],
+    node_type: str,
+    config: WorkflowComparisonConfig,
+    path_prefix: str = "",
+) -> Dict[str, Any]:
+    """
+    Filter parameters based on configuration ignore rules.
+
+    Args:
+        params: Parameter dictionary to filter
+        node_type: Type of the node (for node-specific filtering)
+        config: Configuration with ignore rules
+        path_prefix: Current parameter path (for nested params)
+
+    Returns:
+        Filtered parameter dictionary
+    """
+    filtered = {}
+
+    for key, value in params.items():
+        param_path = f"{path_prefix}.{key}" if path_prefix else key
+
+        # Check if this parameter should be ignored
+        if config.should_ignore_parameter(node_type, param_path):
+            continue
+
+        # Recursively filter nested dictionaries
+        if isinstance(value, dict):
+            nested_filtered = _filter_parameters(value, node_type, config, param_path)
+            if nested_filtered:  # Only include if not empty
+                filtered[key] = nested_filtered
+        else:
+            filtered[key] = value
+
+    return filtered
+
+
+def _is_trigger_node(node: Dict[str, Any]) -> bool:
+    """
+    Detect if a node is a trigger node.
+
+    Args:
+        node: Node dictionary
+
+    Returns:
+        True if node is a trigger
+    """
+    node_type = node.get("type", "").lower()
+    node_name = node.get("name", "").lower()
+
+    # Check if 'trigger' is in type or name
+    if "trigger" in node_type or "trigger" in node_name:
+        return True
+
+    # Check for known trigger node types that don't have 'trigger' in the name
+    trigger_types = [
+        "webhook",  # n8n-nodes-base.webhook
+        "webhooktrigger",
+        "manualtrigger",
+        "scheduletrigger",
+        "chattrigger",
+        "cron",  # n8n-nodes-base.cron
+    ]
+
+    for trigger_type in trigger_types:
+        if trigger_type in node_type:
+            return True
+
+    return False
+
+
+def get_node_data(graph: nx.DiGraph, node_name: str) -> Dict[str, Any]:
+    """
+    Get all data for a node from the graph.
+
+    Args:
+        graph: NetworkX graph
+        node_name: Name of the node
+
+    Returns:
+        Dictionary with node attributes
+    """
+    if node_name not in graph:
+        return {}
+
+    return dict(graph.nodes[node_name])
+
+
+def get_edge_data(graph: nx.DiGraph, source: str, target: str) -> Dict[str, Any]:
+    """
+    Get all data for an edge from the graph.
+
+    Args:
+        graph: NetworkX graph
+        source: Source node name
+        target: Target node name
+
+    Returns:
+        Dictionary with edge attributes
+    """
+    if not graph.has_edge(source, target):
+        return {}
+
+    return dict(graph.edges[source, target])
+
+
+def graph_stats(graph: nx.DiGraph) -> Dict[str, Any]:
+    """
+    Get statistics about a workflow graph.
+
+    Args:
+        graph: NetworkX graph
+
+    Returns:
+        Dictionary with graph statistics
+    """
+    return {
+        "node_count": graph.number_of_nodes(),
+        "edge_count": graph.number_of_edges(),
+        "trigger_count": sum(
+            1 for _, data in graph.nodes(data=True) if data.get("is_trigger", False)
+        ),
+        "node_types": list(
+            set(data.get("type", "unknown") for _, data in graph.nodes(data=True))
+        ),
+        "is_connected": nx.is_weakly_connected(graph)
+        if graph.number_of_nodes() > 0
+        else False,
+    }

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/src/similarity.py

@@ -0,0 +1,501 @@
+"""
+Calculate workflow similarity using graph edit distance.
+"""
+
+import networkx as nx
+from typing import Dict, List, Any, Optional
+from src.config_loader import WorkflowComparisonConfig
+from src.cost_functions import (
+    node_substitution_cost,
+    node_deletion_cost,
+    node_insertion_cost,
+    edge_substitution_cost,
+    edge_deletion_cost,
+    edge_insertion_cost,
+    get_parameter_diff,
+)
+
+
+def calculate_graph_edit_distance(
+    g1: nx.DiGraph, g2: nx.DiGraph, config: WorkflowComparisonConfig
+) -> Dict[str, Any]:
+    """
+    Calculate graph edit distance with custom cost functions.
+
+    Args:
+        g1: First workflow graph (generated)
+        g2: Second workflow graph (ground truth)
+        config: Configuration with cost weights
+
+    Returns:
+        Dictionary with:
+            - similarity_score: 0-1 (1 = identical)
+            - edit_cost: Total cost of edits
+            - max_possible_cost: Theoretical maximum cost
+            - top_edits: List of most important edit operations
+    """
+    # Handle empty graphs
+    if g1.number_of_nodes() == 0 and g2.number_of_nodes() == 0:
+        return {
+            "similarity_score": 1.0,
+            "edit_cost": 0.0,
+            "max_possible_cost": 0.0,
+            "top_edits": [],
+        }
+
+    # Relabel graphs to use structural IDs instead of node names
+    # This ensures nodes are matched by type/position, not by name
+    g1_relabeled, g1_mapping = _relabel_graph_by_structure(g1)
+    g2_relabeled, g2_mapping = _relabel_graph_by_structure(g2)
+
+    # Create cost function closures with config
+    # NetworkX passes node ATTRIBUTE DICTS, not node names
+    def node_subst_cost(n1_attrs, n2_attrs):
+        return node_substitution_cost(n1_attrs, n2_attrs, config)
+
+    def node_del_cost(n_attrs):
+        return node_deletion_cost(n_attrs, config)
+
+    def node_ins_cost(n_attrs):
+        return node_insertion_cost(n_attrs, config)
+
+    # Edge match function - returns True if edges are equivalent
+    # This is better than cost functions for preventing false positives
+    def edge_match(e1_attrs, e2_attrs):
+        """Check if two edges match (same connection type or equivalent)"""
+        conn_type1 = e1_attrs.get("connection_type", "main")
+        conn_type2 = e2_attrs.get("connection_type", "main")
+
+        # Exact match
+        if conn_type1 == conn_type2:
+            return True
+
+        # Check for equivalent types in config
+        for equiv_group in config.equivalent_connection_types:
+            if conn_type1 in equiv_group and conn_type2 in equiv_group:
+                return True
+
+        return False
+
+    # Calculate GED using NetworkX
+    # Note: This can be slow for large graphs, but workflow graphs are typically small
+    try:
+        # Use optimize_edit_paths with edge_match instead of edge cost functions
+        # This prevents false positive edge insertions/deletions
+        edit_path_generator = nx.optimize_edit_paths(
+            g1_relabeled,
+            g2_relabeled,
+            node_subst_cost=node_subst_cost,
+            node_del_cost=node_del_cost,
+            node_ins_cost=node_ins_cost,
+            edge_match=edge_match,
+            upper_bound=None,  # Calculate exact
+        )
+
+        # Get the best (first) edit path
+        best_edit_path = None
+        for node_edit_path, edge_edit_path, cost in edit_path_generator:
+            best_edit_path = (node_edit_path, edge_edit_path, cost)
+            break  # Take the first (best) path
+
+        if not best_edit_path:
+            # Fallback to basic calculation
+            edit_cost = _calculate_basic_edit_cost(g1, g2, config)
+            node_edit_path = []
+            edge_edit_path = []
+        else:
+            node_edit_path, edge_edit_path, edit_cost = best_edit_path
+
+        # Extract and rank edit operations
+        # Use the actual edit path from NetworkX if available
+        if best_edit_path:
+            edit_ops = _extract_operations_from_path(
+                node_edit_path,
+                edge_edit_path,
+                g1_relabeled,
+                g2_relabeled,
+                config,
+                g1_mapping,
+                g2_mapping,
+            )
+        else:
+            edit_ops = []
+    except Exception as e:
+        # Fallback if NetworkX GED fails
+        print(f"Warning: GED calculation failed, using fallback: {e}")
+        edit_cost = _calculate_basic_edit_cost(g1, g2, config)
+        edit_ops = []
+
+    # Calculate theoretical maximum cost
+    max_cost = _calculate_max_cost(g1, g2, config)
+
+    # Avoid division by zero
+    if max_cost == 0:
+        similarity_score = 1.0 if edit_cost == 0 else 0.0
+    else:
+        # Similarity score: 1 - (cost / max_cost)
+        similarity_score = max(0.0, min(1.0, 1.0 - (edit_cost / max_cost)))
+
+    return {
+        "similarity_score": similarity_score,
+        "edit_cost": edit_cost,
+        "max_possible_cost": max_cost,
+        "top_edits": sorted(edit_ops, key=lambda x: x["cost"], reverse=True),
+    }
+
+
+def _calculate_basic_edit_cost(
+    g1: nx.DiGraph, g2: nx.DiGraph, config: WorkflowComparisonConfig
+) -> float:
+    """
+    Calculate a basic edit cost when full GED fails.
+    Uses simple node and edge count differences.
+
+    Args:
+        g1: First graph
+        g2: Second graph
+        config: Configuration
+
+    Returns:
+        Estimated edit cost
+    """
+    cost = 0.0
+
+    # Node differences
+    nodes1 = set(g1.nodes())
+    nodes2 = set(g2.nodes())
+
+    # Nodes only in g1 (need to be deleted)
+    deleted_nodes = nodes1 - nodes2
+    cost += len(deleted_nodes) * config.node_deletion_cost
+
+    # Nodes only in g2 (need to be inserted)
+    inserted_nodes = nodes2 - nodes1
+    cost += len(inserted_nodes) * config.node_insertion_cost
+
+    # Nodes in both (might need substitution)
+    common_nodes = nodes1 & nodes2
+    for node in common_nodes:
+        subst_cost = node_substitution_cost(g1.nodes[node], g2.nodes[node], config)
+        cost += subst_cost
+
+    # Edge differences
+    edges1 = set(g1.edges())
+    edges2 = set(g2.edges())
+
+    deleted_edges = edges1 - edges2
+    cost += len(deleted_edges) * config.edge_deletion_cost
+
+    inserted_edges = edges2 - edges1
+    cost += len(inserted_edges) * config.edge_insertion_cost
+
+    return cost
+
+
+def _calculate_max_cost(
+    g1: nx.DiGraph, g2: nx.DiGraph, config: WorkflowComparisonConfig
+) -> float:
+    """
+    Calculate theoretical maximum edit cost.
+    This represents the cost of completely transforming g1 to g2.
+
+    Args:
+        g1: First graph
+        g2: Second graph
+        config: Configuration
+
+    Returns:
+        Maximum possible cost
+    """
+    # Worst case: delete all of g1, insert all of g2
+    delete_cost = (
+        len(g1.nodes()) * config.node_deletion_cost
+        + len(g1.edges()) * config.edge_deletion_cost
+    )
+    insert_cost = (
+        len(g2.nodes()) * config.node_insertion_cost
+        + len(g2.edges()) * config.edge_insertion_cost
+    )
+
+    return delete_cost + insert_cost
+
+
+def _extract_operations_from_path(
+    node_edit_path: List[tuple],
+    edge_edit_path: List[tuple],
+    g1: nx.DiGraph,
+    g2: nx.DiGraph,
+    config: WorkflowComparisonConfig,
+    g1_name_mapping: Dict[str, str],
+    g2_name_mapping: Dict[str, str],
+) -> List[Dict[str, Any]]:
+    """
+    Extract edit operations from NetworkX's edit path.
+
+    Args:
+        node_edit_path: List of node edit tuples (u, v) where:
+            - (u, v): nodes u in g1 and v in g2 are matched/substituted
+            - (u, None): node u in g1 is deleted
+            - (None, v): node v in g2 is inserted
+        edge_edit_path: List of edge edit tuples ((u1, v1), (u2, v2))
+        g1, g2: Relabeled graphs
+        config: Configuration
+        g1_name_mapping, g2_name_mapping: Mappings to original names
+
+    Returns:
+        List of edit operations with descriptions and costs
+    """
+    operations = []
+
+    # Helper to get display name
+    def get_display_name(
+        node_id: str, mapping: Dict[str, str], graph: nx.DiGraph
+    ) -> str:
+        if mapping and node_id in mapping:
+            return mapping[node_id]
+        return graph.nodes[node_id].get("_original_name", node_id)
+
+    # Process node edits
+    for u, v in node_edit_path:
+        if u is None:
+            # Node insertion (v in g2 is inserted)
+            node_data = g2.nodes[v]
+            display_name = get_display_name(v, g2_name_mapping, g2)
+            cost = node_insertion_cost(node_data, config)
+            if cost > 0:
+                operations.append(
+                    {
+                        "type": "node_insert",
+                        "description": f"Add missing node '{display_name}' (type: {node_data.get('type', 'unknown')})",
+                        "cost": cost,
+                        "priority": _determine_priority(
+                            cost, config, node_data, "node_insert"
+                        ),
+                        "node_name": display_name,
+                    }
+                )
+        elif v is None:
+            # Node deletion (u in g1 is deleted)
+            node_data = g1.nodes[u]
+            display_name = get_display_name(u, g1_name_mapping, g1)
+            cost = node_deletion_cost(node_data, config)
+            if cost > 0:
+                operations.append(
+                    {
+                        "type": "node_delete",
+                        "description": f"Remove node '{display_name}' (type: {node_data.get('type', 'unknown')})",
+                        "cost": cost,
+                        "priority": _determine_priority(
+                            cost, config, node_data, "node_delete"
+                        ),
+                        "node_name": display_name,
+                    }
+                )
+        else:
+            # Node substitution (u in g1 matched to v in g2)
+            node1_data = g1.nodes[u]
+            node2_data = g2.nodes[v]
+            display_name = get_display_name(u, g1_name_mapping, g1)
+            cost = node_substitution_cost(node1_data, node2_data, config)
+            if cost > 0:
+                type1 = node1_data.get("type", "unknown")
+                type2 = node2_data.get("type", "unknown")
+
+                operation_data = {
+                    "type": "node_substitute",
+                    "cost": cost,
+                    "priority": _determine_priority(
+                        cost, config, node1_data, "node_substitute"
+                    ),
+                    "node_name": display_name,
+                }
+
+                if type1 != type2:
+                    operation_data["description"] = (
+                        f"Change node '{display_name}' from type '{type1}' to '{type2}'"
+                    )
+                else:
+                    operation_data["description"] = (
+                        f"Update parameters of node '{display_name}' (type: {type1})"
+                    )
+                    # Extract parameter diff for same-type substitutions
+                    params1 = node1_data.get("parameters", {})
+                    params2 = node2_data.get("parameters", {})
+                    if params1 or params2:
+                        param_diff = get_parameter_diff(params1, params2, type1, config)
+                        if param_diff:
+                            operation_data["parameter_diff"] = param_diff
+
+                operations.append(operation_data)
+
+    # Process edge edits
+    # Note: With edge_match function, the GED algorithm should only report
+    # edges that truly differ, so we don't need complex filtering here
+    for e1, e2 in edge_edit_path:
+        if e1 is None:
+            # Edge insertion
+            u2, v2 = e2
+            edge_data = g2.edges[e2]
+            source_display = get_display_name(u2, g2_name_mapping, g2)
+            target_display = get_display_name(v2, g2_name_mapping, g2)
+            cost = edge_insertion_cost(edge_data, config)
+            if cost > 0:
+                operations.append(
+                    {
+                        "type": "edge_insert",
+                        "description": f"Add missing connection from '{source_display}' to '{target_display}'",
+                        "cost": cost,
+                        "priority": _determine_priority(cost, config),
+                    }
+                )
+        elif e2 is None:
+            # Edge deletion
+            u1, v1 = e1
+            edge_data = g1.edges[e1]
+            source_display = get_display_name(u1, g1_name_mapping, g1)
+            target_display = get_display_name(v1, g1_name_mapping, g1)
+            cost = edge_deletion_cost(edge_data, config)
+            if cost > 0:
+                operations.append(
+                    {
+                        "type": "edge_delete",
+                        "description": f"Remove connection from '{source_display}' to '{target_display}'",
+                        "cost": cost,
+                        "priority": _determine_priority(cost, config),
+                    }
+                )
+        else:
+            # Edge substitution
+            u1, v1 = e1
+            u2, v2 = e2
+            edge1_data = g1.edges[e1]
+            edge2_data = g2.edges[e2]
+            cost = edge_substitution_cost(edge1_data, edge2_data, config)
+            if cost > 0:
+                source_display = get_display_name(u1, g1_name_mapping, g1)
+                target_display = get_display_name(v1, g1_name_mapping, g1)
+                operations.append(
+                    {
+                        "type": "edge_substitute",
+                        "description": f"Update connection from '{source_display}' to '{target_display}'",
+                        "cost": cost,
+                        "priority": _determine_priority(cost, config),
+                    }
+                )
+
+    return operations
+
+
+def _determine_priority(
+    cost: float,
+    config: WorkflowComparisonConfig,
+    node_data: Optional[Dict[str, Any]] = None,
+    operation_type: Optional[str] = None,
+) -> str:
+    """
+    Determine priority level based on cost, node type, and operation.
+
+    Args:
+        cost: Edit operation cost
+        config: Configuration
+        node_data: Optional node data to check if it's a trigger
+        operation_type: Type of operation (node_insert, node_delete, node_substitute, etc.)
+
+    Returns:
+        Priority level: 'critical', 'major', or 'minor'
+    """
+    # Critical: trigger deletions/insertions (but not minor parameter updates)
+    if node_data and node_data.get("is_trigger", False):
+        if operation_type in ("node_insert", "node_delete"):
+            return "critical"
+
+    # Critical: trigger mismatches and high-cost operations
+    if cost >= config.node_substitution_trigger * 0.8:
+        return "critical"
+    elif cost >= config.node_substitution_different_type * 0.8:
+        return "major"
+    else:
+        return "minor"
+
+
+def _relabel_graph_by_structure(graph: nx.DiGraph) -> tuple[nx.DiGraph, Dict[str, str]]:
+    """
+    Relabel graph nodes using structural IDs instead of names.
+
+    This ensures nodes are matched by their type and position in the workflow,
+    not by their display names. The original name is preserved as a node attribute.
+
+    Args:
+        graph: Original graph with name-based node IDs
+
+    Returns:
+        Tuple of (relabeled_graph, mapping_dict) where:
+        - relabeled_graph: Graph with structural IDs
+        - mapping_dict: Maps new IDs back to original names
+    """
+    # Sort nodes by structural properties for consistent matching
+    nodes_with_data = list(graph.nodes(data=True))
+
+    # Define sorting key based on structural properties
+    def node_sort_key(node_tuple):
+        name, data = node_tuple
+        return (
+            data.get("type", ""),  # Sort by type for consistency
+            -graph.out_degree(name),  # Then by out-degree (descending)
+            -graph.in_degree(name),  # Then by in-degree (descending)
+            name,  # Finally by name for deterministic ordering
+        )
+
+    # Separate and sort triggers and non-triggers
+    triggers = sorted(
+        [
+            (name, data)
+            for name, data in nodes_with_data
+            if data.get("is_trigger", False)
+        ],
+        key=node_sort_key,
+    )
+    non_triggers = sorted(
+        [
+            (name, data)
+            for name, data in nodes_with_data
+            if not data.get("is_trigger", False)
+        ],
+        key=node_sort_key,
+    )
+
+    # Create new labels: trigger_0, trigger_1, node_0, node_1, etc.
+    mapping = {}
+    reverse_mapping = {}
+
+    for i, (original_name, _) in enumerate(triggers):
+        new_label = f"trigger_{i}"
+        mapping[original_name] = new_label
+        reverse_mapping[new_label] = original_name
+
+    for i, (original_name, _) in enumerate(non_triggers):
+        new_label = f"node_{i}"
+        mapping[original_name] = new_label
+        reverse_mapping[new_label] = original_name
+
+    # Create relabeled graph - this preserves all node attributes
+    relabeled = nx.relabel_nodes(graph, mapping, copy=True)
+
+    # Store original names in node attributes for matching
+    # This helps the GED algorithm match nodes correctly
+    for new_label, original_name in reverse_mapping.items():
+        if new_label in relabeled.nodes:
+            relabeled.nodes[new_label]["_original_name"] = original_name
+            # Add a normalized name hash to help with matching nodes of the same type
+            # Normalize by replacing smart quotes with regular quotes for comparison
+            # U+2018 (') -> U+0027 ('), U+2019 (') -> U+0027 (')
+            # U+201C (") -> U+0022 ("), U+201D (") -> U+0022 (")
+            normalized_name = original_name.replace("\u2018", "'").replace(
+                "\u2019", "'"
+            )
+            normalized_name = normalized_name.replace("\u201c", '"').replace(
+                "\u201d", '"'
+            )
+            relabeled.nodes[new_label]["_name_hash"] = hash(normalized_name)
+
+    return relabeled, reverse_mapping

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/tests/__init__.py

@@ -0,0 +1 @@
+"""Tests for n8n workflow comparison"""

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/tests/test_graph_builder.py

@@ -0,0 +1,161 @@
+"""
+Tests for graph_builder module.
+"""
+
+from src.graph_builder import build_workflow_graph, graph_stats, _is_trigger_node
+from src.config_loader import WorkflowComparisonConfig
+
+
+def test_build_simple_workflow_graph():
+    """Test building graph from simple workflow"""
+    workflow = {
+        "name": "Test Workflow",
+        "nodes": [
+            {
+                "id": "1",
+                "name": "Trigger",
+                "type": "n8n-nodes-base.webhook",
+                "parameters": {"path": "/test"},
+            },
+            {
+                "id": "2",
+                "name": "Process",
+                "type": "n8n-nodes-base.code",
+                "parameters": {},
+            },
+        ],
+        "connections": {
+            "Trigger": {"main": [[{"node": "Process", "type": "main", "index": 0}]]}
+        },
+    }
+
+    graph = build_workflow_graph(workflow)
+
+    assert graph.number_of_nodes() == 2
+    assert graph.number_of_edges() == 1
+    assert "Trigger" in graph.nodes
+    assert "Process" in graph.nodes
+    assert graph.has_edge("Trigger", "Process")
+
+
+def test_build_graph_with_filtering():
+    """Test that ignored nodes are filtered out"""
+    workflow = {
+        "name": "Test Workflow",
+        "nodes": [
+            {
+                "id": "1",
+                "name": "Note",
+                "type": "n8n-nodes-base.stickyNote",
+                "parameters": {"content": "This is a note"},
+            },
+            {
+                "id": "2",
+                "name": "Trigger",
+                "type": "n8n-nodes-base.webhook",
+                "parameters": {},
+            },
+        ],
+        "connections": {},
+    }
+
+    config = WorkflowComparisonConfig()
+    config.ignored_node_types.add("n8n-nodes-base.stickyNote")
+
+    graph = build_workflow_graph(workflow, config)
+
+    # Sticky note should be filtered out
+    assert graph.number_of_nodes() == 1
+    assert "Trigger" in graph.nodes
+    assert "Note" not in graph.nodes
+
+
+def test_parameter_filtering():
+    """Test that ignored parameters are filtered"""
+    workflow = {
+        "name": "Test",
+        "nodes": [
+            {
+                "id": "1",
+                "name": "Node1",
+                "type": "test.node",
+                "position": [100, 200],
+                "parameters": {
+                    "important": "value",
+                    "position": [100, 200],
+                    "id": "123",
+                },
+            }
+        ],
+        "connections": {},
+    }
+
+    config = WorkflowComparisonConfig()
+    config.ignored_global_parameters = {"position", "id"}
+
+    graph = build_workflow_graph(workflow, config)
+
+    node_data = graph.nodes["Node1"]
+    params = node_data["parameters"]
+
+    assert "important" in params
+    assert "position" not in params
+    assert "id" not in params
+
+
+def test_is_trigger_node():
+    """Test trigger node detection"""
+    trigger_node = {"type": "n8n-nodes-base.webhook", "name": "Webhook Trigger"}
+    assert _is_trigger_node(trigger_node) is True
+
+    regular_node = {"type": "n8n-nodes-base.httpRequest", "name": "HTTP Request"}
+    assert _is_trigger_node(regular_node) is False
+
+
+def test_graph_stats():
+    """Test graph statistics calculation"""
+    workflow = {
+        "name": "Test",
+        "nodes": [
+            {
+                "id": "1",
+                "name": "Trigger",
+                "type": "n8n-nodes-base.manualTrigger",
+                "parameters": {},
+            },
+            {
+                "id": "2",
+                "name": "Node1",
+                "type": "n8n-nodes-base.code",
+                "parameters": {},
+            },
+            {
+                "id": "3",
+                "name": "Node2",
+                "type": "n8n-nodes-base.code",
+                "parameters": {},
+            },
+        ],
+        "connections": {
+            "Trigger": {"main": [[{"node": "Node1", "type": "main", "index": 0}]]},
+            "Node1": {"main": [[{"node": "Node2", "type": "main", "index": 0}]]},
+        },
+    }
+
+    graph = build_workflow_graph(workflow)
+    stats = graph_stats(graph)
+
+    assert stats["node_count"] == 3
+    assert stats["edge_count"] == 2
+    assert stats["trigger_count"] == 1
+    assert stats["is_connected"] is True
+
+
+def test_empty_workflow():
+    """Test building graph from empty workflow"""
+    workflow = {"name": "Empty", "nodes": [], "connections": {}}
+
+    graph = build_workflow_graph(workflow)
+
+    assert graph.number_of_nodes() == 0
+    assert graph.number_of_edges() == 0

packages/@n8n/ai-workflow-builder.ee/evaluations/programmatic/python/tests/test_similarity.py

@@ -0,0 +1,328 @@
+"""
+Tests for similarity module.
+"""
+
+from src.graph_builder import build_workflow_graph
+from src.similarity import calculate_graph_edit_distance
+from src.config_loader import WorkflowComparisonConfig
+
+
+def test_identical_workflows():
+    """Test that identical workflows have 100% similarity"""
+    workflow = {
+        "name": "Test",
+        "nodes": [
+            {
+                "id": "1",
+                "name": "Trigger",
+                "type": "n8n-nodes-base.webhook",
+                "parameters": {"path": "/test"},
+            }
+        ],
+        "connections": {},
+    }
+
+    config = WorkflowComparisonConfig()
+    g1 = build_workflow_graph(workflow, config)
+    g2 = build_workflow_graph(workflow, config)
+
+    result = calculate_graph_edit_distance(g1, g2, config)
+
+    assert result["similarity_score"] == 1.0
+    assert result["edit_cost"] == 0.0
+    assert len(result["top_edits"]) == 0
+
+
+def test_empty_workflows():
+    """Test that empty workflows are identical"""
+    workflow = {"name": "Empty", "nodes": [], "connections": {}}
+
+    config = WorkflowComparisonConfig()
+    g1 = build_workflow_graph(workflow, config)
+    g2 = build_workflow_graph(workflow, config)
+
+    result = calculate_graph_edit_distance(g1, g2, config)
+
+    assert result["similarity_score"] == 1.0
+    assert result["edit_cost"] == 0.0
+
+
+def test_missing_node():
+    """Test similarity when one workflow is missing a node"""
+    workflow1 = {
+        "name": "Test1",
+        "nodes": [{"id": "1", "name": "Node1", "type": "test.node", "parameters": {}}],
+        "connections": {},
+    }
+
+    workflow2 = {
+        "name": "Test2",
+        "nodes": [
+            {"id": "1", "name": "Node1", "type": "test.node", "parameters": {}},
+            {"id": "2", "name": "Node2", "type": "test.node", "parameters": {}},
+        ],
+        "connections": {},
+    }
+
+    config = WorkflowComparisonConfig()
+    g1 = build_workflow_graph(workflow1, config)
+    g2 = build_workflow_graph(workflow2, config)
+
+    result = calculate_graph_edit_distance(g1, g2, config)
+
+    # Should have less than 100% similarity
+    assert result["similarity_score"] < 1.0
+    # Should have edit operations
+    assert len(result["top_edits"]) > 0
+    # Should have a node insertion edit
+    assert any(edit["type"] == "node_insert" for edit in result["top_edits"])
+
+
+def test_trigger_mismatch():
+    """Test that trigger mismatches have high cost"""
+    workflow1 = {
+        "name": "Test1",
+        "nodes": [
+            {
+                "id": "1",
+                "name": "Trigger",
+                "type": "n8n-nodes-base.webhook",
+                "parameters": {},
+            }
+        ],
+        "connections": {},
+    }
+
+    workflow2 = {
+        "name": "Test2",
+        "nodes": [
+            {
+                "id": "1",
+                "name": "Trigger",
+                "type": "n8n-nodes-base.manualTrigger",
+                "parameters": {},
+            }
+        ],
+        "connections": {},
+    }
+
+    config = WorkflowComparisonConfig()
+    g1 = build_workflow_graph(workflow1, config)
+    g2 = build_workflow_graph(workflow2, config)
+
+    result = calculate_graph_edit_distance(g1, g2, config)
+
+    # Trigger mismatch should result in low similarity
+    assert result["similarity_score"] < 0.8
+
+    # NetworkX may choose delete+insert (cost 20) over substitution (cost 50)
+    # but the important thing is that we detect it as a critical issue
+    assert result["edit_cost"] >= (
+        config.node_deletion_cost + config.node_insertion_cost
+    )
+
+    # Should have critical priority edit in the top edits
+    assert len(result["top_edits"]) > 0
+    assert any(edit["priority"] == "critical" for edit in result["top_edits"])
+
+
+def test_parameter_differences():
+    """Test that parameter differences affect similarity"""
+    workflow1 = {
+        "name": "Test1",
+        "nodes": [
+            {
+                "id": "1",
+                "name": "Node",
+                "type": "test.node",
+                "parameters": {"value": "a"},
+            }
+        ],
+        "connections": {},
+    }
+
+    workflow2 = {
+        "name": "Test2",
+        "nodes": [
+            {
+                "id": "1",
+                "name": "Node",
+                "type": "test.node",
+                "parameters": {"value": "b"},
+            }
+        ],
+        "connections": {},
+    }
+
+    config = WorkflowComparisonConfig()
+    g1 = build_workflow_graph(workflow1, config)
+    g2 = build_workflow_graph(workflow2, config)
+
+    result = calculate_graph_edit_distance(g1, g2, config)
+
+    # Should not be identical due to parameter difference
+    assert result["similarity_score"] < 1.0
+    # But should still be fairly similar (same structure)
+    assert result["similarity_score"] > 0.8
+
+
+def test_connection_difference():
+    """Test that connection differences are detected"""
+    workflow1 = {
+        "name": "Test1",
+        "nodes": [
+            {"id": "1", "name": "Node1", "type": "test.node", "parameters": {}},
+            {"id": "2", "name": "Node2", "type": "test.node", "parameters": {}},
+        ],
+        "connections": {},  # No connections
+    }
+
+    workflow2 = {
+        "name": "Test2",
+        "nodes": [
+            {"id": "1", "name": "Node1", "type": "test.node", "parameters": {}},
+            {"id": "2", "name": "Node2", "type": "test.node", "parameters": {}},
+        ],
+        "connections": {
+            "Node1": {"main": [[{"node": "Node2", "type": "main", "index": 0}]]}
+        },
+    }
+
+    config = WorkflowComparisonConfig()
+    g1 = build_workflow_graph(workflow1, config)
+    g2 = build_workflow_graph(workflow2, config)
+
+    result = calculate_graph_edit_distance(g1, g2, config)
+
+    # Should have lower similarity due to missing connection
+    assert result["similarity_score"] < 1.0
+    # Should have edge insertion in edits
+    assert any(edit["type"] == "edge_insert" for edit in result["top_edits"])
+
+
+def test_trigger_parameter_update_priority():
+    """Test that minor trigger parameter updates are not marked as critical."""
+    from src.config_loader import load_config
+
+    workflow1 = {
+        "name": "Test1",
+        "nodes": [
+            {
+                "id": "1",
+                "name": "Webhook",
+                "type": "n8n-nodes-base.webhook",
+                "parameters": {"path": "test1"},
+            }
+        ],
+        "connections": {},
+    }
+
+    workflow2 = {
+        "name": "Test2",
+        "nodes": [
+            {
+                "id": "1",
+                "name": "Webhook",
+                "type": "n8n-nodes-base.webhook",
+                "parameters": {"path": "test2"},
+            }
+        ],
+        "connections": {},
+    }
+
+    config = load_config("preset:lenient")
+    g1 = build_workflow_graph(workflow1, config)
+    g2 = build_workflow_graph(workflow2, config)
+
+    result = calculate_graph_edit_distance(g1, g2, config)
+
+    # Should have high similarity (just parameter change)
+    assert result["similarity_score"] > 0.9
+
+    # Should have one edit (parameter update)
+    assert len(result["top_edits"]) == 1
+    edit = result["top_edits"][0]
+
+    # Should NOT be critical priority (just a minor parameter change)
+    assert edit["priority"] != "critical"
+    assert edit["type"] == "node_substitute"
+
+
+def test_trigger_deletion_is_critical():
+    """Test that trigger deletions are marked as critical."""
+    from src.config_loader import WorkflowComparisonConfig
+
+    workflow1 = {
+        "name": "Test1",
+        "nodes": [
+            {
+                "id": "1",
+                "name": "Webhook",
+                "type": "n8n-nodes-base.webhook",
+                "parameters": {},
+            },
+            {"id": "2", "name": "Node", "type": "test.node", "parameters": {}},
+        ],
+        "connections": {},
+    }
+
+    workflow2 = {
+        "name": "Test2",
+        "nodes": [{"id": "2", "name": "Node", "type": "test.node", "parameters": {}}],
+        "connections": {},
+    }
+
+    config = WorkflowComparisonConfig()
+    g1 = build_workflow_graph(workflow1, config)
+    g2 = build_workflow_graph(workflow2, config)
+
+    result = calculate_graph_edit_distance(g1, g2, config)
+
+    # Should have lower similarity
+    assert result["similarity_score"] < 0.8
+
+    # Should have a critical priority edit (trigger deletion)
+    assert any(
+        edit["priority"] == "critical" and edit["type"] == "node_delete"
+        for edit in result["top_edits"]
+    )
+
+
+def test_trigger_insertion_is_critical():
+    """Test that trigger insertions are marked as critical."""
+    from src.config_loader import WorkflowComparisonConfig
+
+    workflow1 = {
+        "name": "Test1",
+        "nodes": [{"id": "1", "name": "Node", "type": "test.node", "parameters": {}}],
+        "connections": {},
+    }
+
+    workflow2 = {
+        "name": "Test2",
+        "nodes": [
+            {
+                "id": "1",
+                "name": "Webhook",
+                "type": "n8n-nodes-base.webhook",
+                "parameters": {},
+            },
+            {"id": "2", "name": "Node", "type": "test.node", "parameters": {}},
+        ],
+        "connections": {},
+    }
+
+    config = WorkflowComparisonConfig()
+    g1 = build_workflow_graph(workflow1, config)
+    g2 = build_workflow_graph(workflow2, config)
+
+    result = calculate_graph_edit_distance(g1, g2, config)
+
+    # Should have lower similarity
+    assert result["similarity_score"] < 0.8
+
+    # Should have a critical priority edit (trigger insertion)
+    assert any(
+        edit["priority"] == "critical" and edit["type"] == "node_insert"
+        for edit in result["top_edits"]
+    )

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