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x402-ai-changelog

AI Changelog: Generate a changelog from git commits using AI.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
logNoLog to process
textNoText to process
commitsNoCommits to process

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / text
      Added value: +{
      +  "description": "Text to process",
      +  "type": "string"
      +}
  2. First observed

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations at all, the description carries the full behavioral burden and largely fails: it does not say whether the three inputs are alternatives or combinable, what commit log format is expected, or what the generated changelog looks like. Only the fact that generation is AI-assisted is disclosed.

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?

A single short sentence, front-loaded with the outcome. It is efficient but arguably under-specified rather than deliberately terse, so it falls short of a 5.

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

Completeness2/5

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

For a 3-parameter tool with no annotations and no output schema, the description is not complete enough: the relationship between log/text/commits — the single most important thing an agent must resolve before calling it — is left entirely unexplained.

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 nominally 100%, so the baseline is 3. That said, the schema text ('Log to process', 'Text to process', 'Commits to process') is near-tautological, and the description adds nothing to disambiguate three seemingly overlapping input modes.

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?

States a specific verb (generate) and resource (changelog) plus the input source (git commits) and the AI mechanism. However it does nothing to distinguish itself from the sibling x402-changelog-gen, so an agent must guess between the two.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no mention of the near-identical sibling x402-changelog-gen, and no hint about which of the three inputs should be supplied. The agent is left to infer everything from the name alone.

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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