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Generate Changelog

generate_changelog

Generate a Markdown changelog from real git history, grouped by conventional-commit types into Breaking, Features, Fixes, Other. Optionally scope between two refs.

Instructions

Generate a Markdown changelog from real git history, grouped into Breaking Changes/Features/Fixes/Other via conventional-commit types — a reformatting of commit messages that already exist, never invented entries. Optionally scoped between fromRef/toRef (e.g. two tags).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toRefNo
fromRefNo
projectPathYes
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds valuable transparency by guaranteeing no invented entries ('never invented entries'), which implies a non-fabricating, read-only transformation of git history. Yet it does not explicitly clarify whether the tool writes a file or returns output to stdout, nor does it address edge cases like non-conventional commits or missing git history. This ambiguity prevents a higher score.

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 two sentences with no redundant phrasing. It front-loads the core action and grouping behavior, then adds the scoping option in a clear, compact sentence. Every word earns its place, making it appropriately concise and well-structured.

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 moderate tool complexity and no output schema, the description provides a complete-enough picture: it names the output format ('Markdown changelog'), the grouping categories (Breaking Changes/Features/Fixes/Other), and the optional input refs. It could address edge cases (e.g., behavior when no conventional commits exist) or the exact return/output mode, but for a tool of this simplicity, the description is largely sufficient.

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

Parameters4/5

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

The schema has 0% description coverage, so the description must compensate. It explains the semantics of fromRef/toRef as optional scoping ('Optionally scoped between fromRef/toRef'), giving concrete meaning beyond parameter names. projectPath is not explicitly described, but as a common term it is inferable. This is a strong compensation given the schema's lack of descriptions.

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's function: generating a Markdown changelog from real git history, grouped by conventional-commit types. It uses a specific verb ('generate'), names the resource ('changelog'), and distinguishes from sibling tools like generate_readme or analyze_project. The clarification that it is 'a reformatting of commit messages that already exist, never invented entries' further sharpens the purpose.

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 provides clear context for when to use the tool: it operates on 'real git history' and can be scoped 'between fromRef/toRef (e.g. two tags)'. This helps the agent understand the intended use case. However, it does not explicitly name alternatives or state when not to use it, leaving slight ambiguity relative to sibling tools, but the context is strong enough to infer.

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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