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ahamdjin

Automation Auditor MCP

by ahamdjin

audit_workflow

Audit n8n, Dify, Activepieces, or Trigger.dev workflow exports for static issues before deployment. Paste source; no execution, filesystem access, or external calls.

Instructions

Read-only checks on n8n JSON, Dify DSL, Activepieces JSON or Trigger.dev code.

platform: n8n | dify | activepieces | trigger | auto. Paste an export/source string; no filesystem access, no external calls, no execution. Trigger.dev findings are heuristic and not a substitute for TypeScript checks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYes
platformYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and does so well: it declares read-only behavior, no filesystem access, no external calls, and no execution, and it explicitly warns that Trigger.dev findings are heuristic and not a substitute for TypeScript checks. It omits any statement about output shape or severity, which keeps it below a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Short and front-loaded: the capability statement leads, followed by the platform vocabulary and the safety caveats. The 'platform: ...' fragment is terse but functional; little is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 2-parameter tool with no output schema and no annotations, the description covers input expectations and safety boundaries but never hints at what the audit returns (finding structure, severity, pass/fail). An agent can call it correctly but cannot anticipate the result shape.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and neither parameter has a description or enum, yet the description supplies the valid platform values (n8n | dify | activepieces | trigger | auto) and explains that 'source' is a pasted export/source string. That compensates for most of the schema gap, though it does not clarify format differences between platforms.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb+resource — read-only audits of workflow definitions — and enumerates the exact artifact types it accepts (n8n JSON, Dify DSL, Activepieces JSON, Trigger.dev code). It does not explicitly differentiate itself from the audit_openapi sibling, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied rather than stated: the agent learns it should 'paste an export/source string' and that 'auto' is an acceptable platform value, which conveys the calling context. However, there is no guidance on when to prefer this tool over audit_openapi or preflight_url, and no stated exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.