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delimit_changelog

Generates changelogs from git commits with ledger items or from OpenAPI spec comparisons. Supports markdown, JSON, keepachangelog, and GitHub release formats.

Instructions

Generate a changelog from git commits + ledger, or from API spec changes.

Two modes:

  1. Git mode (pass repo_path): reads git log since last tag, categorizes commits (feat/fix/refactor/docs/test/ci), pulls completed ledger items, and formats as clean Markdown. Works for ANY repo.

  2. Spec mode (pass old_spec + new_spec): compares two OpenAPI specs and produces a changelog of API changes. Original behavior.

Formats: markdown, json, keepachangelog, github-release.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
old_specNoPath to old OpenAPI spec (spec mode only).
new_specNoPath to new OpenAPI spec (spec mode only).
formatNoOutput format (markdown, json, keepachangelog, github-release).markdown
versionNoVersion label for the changelog entry (e.g. "4.1.0").
repo_pathNoPath to a git repository (git mode). When set, uses git log.
since_tagNoGit tag to diff from (default: auto-detect latest tag).
include_ledgerNoPull completed ledger items into changelog (git mode, default true).
output_fileNoWrite changelog to this file path. If CHANGELOG.md, prepends entry.

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 carries full burden. It details git mode behavior (reads git log, categorizes, pulls ledger, formats) and spec mode (compares specs). It also notes output_file prepends to CHANGELOG.md. Could be more thorough on side effects or permissions.

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 well-structured with a clear summary and bullet-style listing of modes. It is concise with no wasted words, using bold headings for readability.

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 8 parameters and two modes, the description covers modes, formats, and output file behavior. It does not discuss errors or limitations, but with an output schema present (per context), return values are not needed. Adequate for agent decision-making.

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?

Schema coverage is 100%, so baseline is 3. The description adds meaning by grouping parameters into modes (repo_path for git mode, old_spec+new_spec for spec mode) and explaining the output_file prepend behavior, exceeding schema 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 generates a changelog from git commits + ledger or from API spec changes. It distinguishes two modes (git and spec) with specific verbs and resources, making it distinct from siblings.

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 explains when to use each mode (git mode with repo_path, spec mode with old_spec+new_spec) and mentions it works for any repo. However, it lacks explicit exclusion of alternatives or when-not-to-use guidance.

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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