mcp-dev-workflow

Commit message

commit_message

Validate and normalize Conventional Commit messages, returning structured results with validity, parsed data, and flags for type, length, or imperative-mood issues.

Instructions

Validate and normalize a Conventional Commit message (type(scope): subject). Returns { valid, normalized, errors, warnings, parsed } and flags type, length and imperative-mood issues.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "message": "<message>"
    },
    "name": "commit_message"
  }
}

Input Schema

Name	Required	Description
`message`	Yes	The commit message to validate (first line is the header).
`allowedTypes`	No	Commit types accepted by the project.
`requireScope`	No	Whether a scope, e.g. (auth), is mandatory.
`maxSubjectLength`	No	Maximum allowed length of the subject.

Output Schema

Name	Required	Description	Default
`valid`	Yes
`errors`	Yes
`parsed`	Yes
`warnings`	Yes
`normalized`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 6, 2026

TDQS

A4/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and it discloses key behaviors: validation, normalization, returning structured fields, and flagging specific issue categories (type, length, imperative mood). It does not mention side effects or authorization, but as a read-only validation tool this is acceptable, and the return details provide meaningful transparency.

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 sentences, front-loaded with the main action, and every phrase adds value—return shape and validation flags are included without redundant explanation.

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

Completeness4/5

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

Given the tool's moderate complexity and the presence of an output schema, the description adequately covers the tool's purpose and behavior. It could mention broader context (e.g., intended workflow) but that's not essential for correct invocation.

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 all parameter meanings are already available in the schema. The description adds no additional parameter-level details beyond that, so it meets the baseline for high coverage.

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 uses a specific verb 'validate and normalize' and explicitly references the Conventional Commit format, which clearly distinguishes it from sibling tools branch_name and pr_checklist. It also outlines the return structure, leaving no ambiguity about the tool's core function.

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 intended use case is implied by the description—validating commit messages—but there is no explicit guidance on when to choose this over branch_name or pr_checklist. No exclusions or alternatives are mentioned.

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

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