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surajfale

Git Commit MCP Server

by surajfale

generate_commit_message

Analyze repository changes to generate a Conventional Commit message using AI, with heuristic fallback for reliable output.

Instructions

Analyze changes and generate a Conventional Commit message using AI.

  • For remote repositories, only SSH URLs are allowed.

  • Uses OpenAI gpt-4o-mini (configurable) when ENABLE_AI=true.

  • Falls back to heuristic generator on failure or when AI is disabled.

Returns: { success, commit_message, files_changed, message, error? }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repository_pathNo.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description discloses key behaviors: AI model (gpt-4o-mini), configurability via ENABLE_AI, fallback to heuristic, SSH-only constraint, and return format. It does not mention any destructive actions, which is appropriate. The behavioral coverage is good.

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?

The description is concise (about 50 words), well-structured with bullet points, and front-loads the main action. Every sentence adds value, and the return format is clearly outlined.

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 simplicity (one parameter, no annotations, has output schema) and the described behaviors (AI fallback, SSH constraint), the description is nearly complete. It could explicitly mention the repository_path parameter, but the default '.'' and the context of analyzing changes mitigates this gap.

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

Parameters2/5

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

The input schema has 0% parameter description coverage, and the tool description does not mention the 'repository_path' parameter at all. The agent must infer its purpose (the path to the git repository) from context, which is insufficient for a single-parameter tool.

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 clearly states the verb ('Analyze changes and generate') and the resource ('a Conventional Commit message'). It distinguishes itself from the sibling tool 'git_commit_and_push' by focusing solely on message generation, implying no commit/push action.

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 description implies when to use the tool (to generate a commit message) but does not explicitly contrast with the sibling tool or state when not to use it. It does mention the SSH URL constraint for remote repos, which is helpful context.

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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