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CSOAI-ORG

Commit Message AI MCP

by CSOAI-ORG
OverviewSchemaRelated ServersScoreDiscussions
Python

generate_commit_message

Generate conventional commit messages from your change descriptions. Auto-detects type, scope, and breaking changes to produce standardized commit messages.

Instructions

Generate a conventional commit message from a description. Auto-detects type, scope, and breaking changes.

Behavior: This tool generates structured output without modifying external systems. Output is deterministic for identical inputs. No side effects. Free tier: 10/day rate limit. Pro tier: unlimited. No authentication required for basic usage.

When to use: Use this tool when you need structured analysis or classification of inputs against established frameworks or standards.

When NOT to use: Not suitable for real-time production decision-making without human review of results.

Args: changes_description (str): The changes description to analyze or process. commit_type (str): The commit type to analyze or process. scope (str): The scope to analyze or process. breaking (bool): The breaking to analyze or process. api_key (str): The api key to analyze or process.

Behavioral Transparency: - Side Effects: This tool is read-only and produces no side effects. It does not modify any external state, databases, or files. All output is computed in-memory and returned directly to the caller. - Authentication: No authentication required for basic usage. Pro/Enterprise tiers require a valid MEOK API key passed via the MEOK_API_KEY environment variable. - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are included in responses (X-RateLimit-Remaining, X-RateLimit-Reset). - Error Handling: Returns structured error objects with 'error' key on failure. Never raises unhandled exceptions. Invalid inputs return descriptive validation errors. - Idempotency: Fully idempotent — calling with the same inputs always produces the same output. Safe to retry on timeout or transient failure. - Data Privacy: No input data is stored, logged, or transmitted to external services. All processing happens locally within the MCP server process.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
changes_descriptionYes
commit_typeNoauto
scopeNo
breakingNo
api_keyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A3.8/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden. It includes a dedicated 'Behavioral Transparency' section covering read-only operation, no side effects, deterministic output, rate limits, error handling, idempotency, and data privacy. This is comprehensive.

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

Conciseness3/5

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

The description is well-organized with sections and bullet points, but contains redundancy (e.g., 'Behavior' paragraph overlaps with 'Behavioral Transparency') and a verbose 'Args' section that provides no useful information. Could be more concise.

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 behavioral aspects are well-covered, but the lack of parameter explanation is a significant gap. The output schema exists, so return value details are not required, but the description could mention the output format. Overall, incomplete due to poor parameter semantics.

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

Parameters1/5

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

Schema description coverage is 0%. The 'Args' section merely restates parameter names and types without adding meaning (e.g., 'changes_description (str): The changes description to analyze or process.'). This adds no value over the schema.

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 tool generates a conventional commit message from a description, with auto-detection of type, scope, and breaking changes. This distinguishes it from siblings like 'analyze_diff' or 'suggest_type'.

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

Usage Guidelines4/5

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

The description includes explicit 'When to use' and 'When NOT to use' sections, advising use for structured analysis and cautioning against production use without human review. However, it does not directly compare to sibling tools.

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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