Skip to main content
Glama
duynghien

n8n-custom-mcp

by duynghien

lint_workflow

Lint n8n workflows to identify best-practice violations like orphaned nodes, missing error handling, generic names, hardcoded secrets, and unbounded loops. Get a score and list of issues.

Instructions

Lint workflow for best practices. Checks: orphaned nodes, missing error handling, generic node names, hardcoded secrets, and loops without limits. Returns score (0-100) and list of issues.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workflowYesWorkflow object to lint

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.2.1

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations provided, the description carries the full disclosure burden and does it well: it lists the exact checks performed and the return shape (score and issues). It stops short of explicitly stating that the operation is non-mutating, though 'lint' idiomatically implies read-only static analysis, and it does not describe the internal structure of individual issues.

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

Conciseness5/5

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

Two compact sentences with zero filler: the first states the core purpose, the second packs in the check list and return format. Everything present earns its place, and the most identifying information is front-loaded.

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?

The single-parameter design and lack of output schema keep the burden modest, and the description covers the checks and return shape. However, it omits details about what an issue object contains (severity, node reference, type) and does not clarify the boundary against sibling validation tools, leaving meaningful ambiguity in the validation sibling cluster.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline of 3 applies. The schema already documents the 'workflow' parameter with required name and nodes plus optional connections. The tool description adds nothing about the parameter itself, focusing instead on the lint checks, which is acceptable given the schema already carries that weight.

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

Purpose5/5

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

The description states a specific verb ('lint') and resource ('workflow'), enumerates five concrete check categories (orphaned nodes, missing error handling, generic node names, hardcoded secrets, loop limits), and specifies the output (score 0-100 plus issue list). This scope clearly differentiates it from the validation siblings, which target structure, credentials, and expressions rather than best-practice scoring.

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?

The usage context is implied: a workflow object is passed in and evaluated against best practices, which signals a quality-review use case. However, there is no explicit when/when-not guidance or named alternatives, and with closely related siblings like validate_workflow_structure and suggest_workflow_improvements, an agent must infer which tool is appropriate for which scenario.

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