| name | execution-monitoring |
| description | Workflow execution, monitoring, and debugging. This skill should be used when the user asks to run a workflow, check execution status, view execution history, or debug workflow errors. |
Execution & Monitoring
This skill covers running and monitoring n8n workflow executions — triggering runs, checking status, debugging failures, and understanding execution data.
Available Tools
| Tool | Description |
|---|
execute_workflow | Trigger a workflow execution |
list_executions | List recent executions |
get_execution | Get detailed execution results |
activate_workflow | Activate (enable trigger-based execution) |
deactivate_workflow | Deactivate (disable triggers) |
Executing Workflows
Manual Execution
Tool: execute_workflow
Input: {
"workflow_id": "wf_abc123"
}
Execution with Input Data
Tool: execute_workflow
Input: {
"workflow_id": "wf_abc123",
"data": {
"name": "Test User",
"email": "test@example.com"
}
}
Listing Executions
All Recent Executions
Tool: list_executions
Input: {
"limit": 20
}
Filter by Workflow
Tool: list_executions
Input: {
"workflow_id": "wf_abc123",
"limit": 10
}
Filter by Status
Tool: list_executions
Input: {
"status": "error",
"limit": 10
}
Execution statuses: success, error, waiting, running
Execution Details
Tool: get_execution
Input: {
"execution_id": "exec_xyz789"
}
Returns:
- Execution status (success/error)
- Start time, end time, duration
- Node-by-node output data
- Error details (if failed)
Common Workflows
Execute and Verify
1. execute_workflow(workflow_id) -> Get execution_id
2. get_execution(execution_id) -> Check status and outputs
3. If error: identify failing node and error message
Debug Failed Execution
1. list_executions(workflow_id, status="error") -> Find failed runs
2. get_execution(execution_id) -> See full error details
3. Identify:
- Which node failed
- What error message
- What input data the node received
4. get_workflow(workflow_id) -> Get workflow to fix
5. Fix the issue (update node parameters, add validation, etc.)
6. update_workflow(workflow_id, fixed_data) -> Save fix
7. execute_workflow(workflow_id) -> Re-test
Monitor Workflow Health
1. list_executions(workflow_id, limit=50) -> Get recent history
2. Count success vs error executions
3. Identify patterns (time of failure, specific nodes)
4. Report findings and suggest improvements
Activation Lifecycle
| State | Trigger-based execution | Manual execution |
|---|
| Active | Triggers fire automatically | Can also run manually |
| Inactive | Triggers do NOT fire | Can still run manually |
// Enable trigger-based execution
activate_workflow(workflow_id)
// Disable triggers (manual execution still works)
deactivate_workflow(workflow_id)
Error Types
| Error | Common Cause | Fix |
|---|
| Authentication | Invalid/expired credentials | Update credential |
| Connection refused | Wrong URL or service down | Check URL and service status |
| Timeout | Slow external API | Increase timeout or add retry |
| Invalid input | Missing/wrong data format | Add validation node before |
| Rate limit | Too many API calls | Add Wait node or batch processing |
Retry Failed Executions
Manual Retry
1. list_executions(workflow_id, status="error") → Find failed execution
2. get_execution(execution_id) → Understand the failure
3. If issue is transient (API timeout, rate limit):
execute_workflow(workflow_id) → Re-run the workflow
4. If issue is in the data:
execute_workflow(workflow_id, input_data) → Re-run with corrected data
Execution with Input Data
Tool: execute_workflow
Input: {
"workflow_id": "wf_abc123",
"data": {
"key": "value",
"orderId": 42
}
}
Best Practices
- Test before activating — use
execute_workflow with test data
- Check execution details — don't assume success, verify node outputs
- Monitor error rate — regularly check
list_executions(status="error")
- Use meaningful test data — test with realistic inputs
- Debug from execution data — node outputs show exactly what went wrong
- Deactivate flapping workflows — disable workflows that keep failing until fixed
- Retry transient failures — API timeouts and rate limits often resolve on retry
- Set up error notifications — configure Error Trigger workflow for critical processes