# Audit every workflow on your n8n instance in one run

**Use case:** 

Sweep a whole n8n instance in one run and get a ranked list of security, reliability and correctness problems across every workflow, plus a health score out of 100 for each. Open the task, add your instance URL and API key, and run it - the Actor reads GET /api/v1/workflows only, so it never writes and never sees a credential value. Ships prefilled with three sample workflows.

## Input

```json
{
  "workflowJson": {
    "workflows": [
      {
        "id": "8xKp2Vn7RtLqZxYb",
        "name": "Stripe to Slack alerts",
        "nodes": [
          {
            "id": "1",
            "name": "Stripe webhook",
            "type": "n8n-nodes-base.webhook",
            "typeVersion": 2,
            "position": [
              0,
              0
            ],
            "parameters": {
              "path": "stripe-events",
              "httpMethod": "POST"
            }
          },
          {
            "id": "2",
            "name": "Post to Slack",
            "type": "n8n-nodes-base.httpRequest",
            "typeVersion": 4.2,
            "position": [
              240,
              0
            ],
            "parameters": {
              "url": "https://slack.com/api/chat.postMessage",
              "method": "POST",
              "sendHeaders": true,
              "headerParameters": {
                "parameters": [
                  {
                    "name": "Authorization",
                    "value": "Bearer xoxb-7781204935-6612840937261-Lq8ZmXrTwYbHf3TgKp2V"
                  }
                ]
              },
              "options": {}
            }
          }
        ],
        "connections": {
          "Stripe webhook": {
            "main": [
              [
                {
                  "node": "Post to Slack",
                  "type": "main",
                  "index": 0
                }
              ]
            ]
          }
        },
        "settings": {}
      },
      {
        "id": "3mQr9TzWfNpXcVdE",
        "name": "Nightly CRM sync",
        "nodes": [
          {
            "id": "1",
            "name": "Cron",
            "type": "n8n-nodes-base.cron",
            "typeVersion": 1,
            "position": [
              0,
              0
            ],
            "parameters": {
              "triggerTimes": {
                "item": [
                  {
                    "mode": "everyDay",
                    "hour": 3
                  }
                ]
              }
            }
          },
          {
            "id": "2",
            "name": "Fetch contacts",
            "type": "n8n-nodes-base.httpRequest",
            "typeVersion": 3,
            "position": [
              240,
              0
            ],
            "parameters": {
              "url": "https://api.crm.internal/contacts",
              "options": {}
            }
          },
          {
            "id": "3",
            "name": "Upsert rows",
            "type": "n8n-nodes-base.postgres",
            "typeVersion": 2.4,
            "position": [
              480,
              0
            ],
            "parameters": {
              "operation": "executeQuery",
              "query": "=INSERT INTO contacts (email) VALUES ('{{ $json.email }}')",
              "options": {}
            },
            "credentials": {
              "postgres": {
                "id": "5",
                "name": "Postgres account"
              }
            }
          }
        ],
        "connections": {
          "Cron": {
            "main": [
              [
                {
                  "node": "Fetch contacts",
                  "type": "main",
                  "index": 0
                }
              ]
            ]
          },
          "Fetch contacts": {
            "main": [
              [
                {
                  "node": "Upsert rows",
                  "type": "main",
                  "index": 0
                }
              ]
            ]
          }
        },
        "settings": {}
      },
      {
        "id": "5jHn4BvYqKsLmTrU",
        "name": "Support AI agent",
        "nodes": [
          {
            "id": "1",
            "name": "When chat message received",
            "type": "@n8n/n8n-nodes-langchain.chatTrigger",
            "typeVersion": 1.1,
            "position": [
              0,
              0
            ],
            "parameters": {}
          },
          {
            "id": "2",
            "name": "AI Agent",
            "type": "@n8n/n8n-nodes-langchain.agent",
            "typeVersion": 1.7,
            "position": [
              240,
              0
            ],
            "parameters": {}
          },
          {
            "id": "3",
            "name": "OpenAI Chat Model",
            "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
            "typeVersion": 1,
            "position": [
              180,
              200
            ],
            "parameters": {},
            "credentials": {
              "openAiApi": {
                "id": "8",
                "name": "OpenAi account"
              }
            }
          },
          {
            "id": "4",
            "name": "Window Buffer Memory",
            "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
            "typeVersion": 1.2,
            "position": [
              340,
              200
            ],
            "parameters": {}
          },
          {
            "id": "5",
            "name": "Draft notes",
            "type": "n8n-nodes-base.stickyNote",
            "typeVersion": 1,
            "position": [
              600,
              0
            ],
            "parameters": {
              "content": "TODO: add a fallback model"
            }
          }
        ],
        "connections": {
          "When chat message received": {
            "main": [
              [
                {
                  "node": "AI Agent",
                  "type": "main",
                  "index": 0
                }
              ]
            ]
          },
          "OpenAI Chat Model": {
            "ai_languageModel": [
              [
                {
                  "node": "AI Agent",
                  "type": "ai_languageModel",
                  "index": 0
                }
              ]
            ]
          },
          "Window Buffer Memory": {
            "ai_memory": [
              [
                {
                  "node": "AI Agent",
                  "type": "ai_memory",
                  "index": 0
                }
              ]
            ]
          }
        },
        "settings": {
          "errorWorkflow": "err-1"
        }
      }
    ]
  },
  "workflowUrls": [],
  "workflowIds": [],
  "activeOnly": false,
  "ruleSet": "all",
  "minSeverity": "low",
  "ignoreRules": [],
  "includeReport": false
}
```

## Output

```json
{
  "severity": {
    "label": "Severity",
    "format": "string"
  },
  "rule": {
    "label": "Rule ID",
    "format": "string"
  },
  "ruleTitle": {
    "label": "Rule",
    "format": "string"
  },
  "category": {
    "label": "Category",
    "format": "string"
  },
  "workflowName": {
    "label": "Workflow",
    "format": "string"
  },
  "nodeName": {
    "label": "Node",
    "format": "string"
  },
  "nodeType": {
    "label": "Node type",
    "format": "string"
  },
  "message": {
    "label": "Finding",
    "format": "string"
  },
  "parameterPath": {
    "label": "Parameter",
    "format": "string"
  },
  "evidence": {
    "label": "Evidence (masked)",
    "format": "string"
  },
  "remediation": {
    "label": "How to fix",
    "format": "string"
  },
  "docsUrl": {
    "label": "Docs",
    "format": "string"
  }
}
```

## About this Actor

This example demonstrates how to use [n8n Workflow Auditor - Linter & Security Review](https://apify.com/mediocre_interest/n8n-workflow-auditor.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/mediocre_interest/n8n-workflow-auditor.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
This Task's input is already configured above — use it as-is rather than inventing a new one.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/mediocre_interest/n8n-workflow-auditor.md

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).