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Agent skill

API Review

by athola in athola/claude-night-market

Evaluates API surface design, consistency, and exemplar alignment.

MITAuto-check passedDevelopment

Install API Review

skills CLI
$ npx skills add athola/claude-night-market --skill api-review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install athola/claude-night-market api-review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/athola/claude-night-market.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/pensive/skills/api-review .claude/skills/api-review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
api-review
GitHub stars
342
Token cost
~1.3k tokens
SKILL.md length
542 words
Files
4
Skills in repo
159
Repo updated
First seen
Licence
MIT

At a glance

Evaluates API surface design, consistency, and exemplar alignment.

  • Works in 5 steps: Surface Inventory → Exemplar Research → Consistency Audit → …
  • Reviewing public API changes
  • SKILL.md covers When NOT To Use, Usage, Required Progress Tracking and Workflow, plus 6 more sections
  • Calls git

What it does

API Review is an agent skill from athola/claude-night-market. Evaluates API surface design, consistency, and exemplar alignment. Use when reviewing public API changes or before releasing a new API surface.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files (for example `modules/consistency-audit.md`, `modules/exemplar-research.md` and `modules/surface-inventory.md`).

It sits in Development. The repository describes itself as: 23 Claude Code plugins: TDD enforcement hooks, git/PR workflows, spec-driven development, code review, project lifecycle, fix-from-error, maintenance automation, context… The licence is MIT.

When your agent uses it

  • Reviewing public API changes
  • Before releasing a new API surface

Example prompts

  • “Use the api-review skill to evaluate API surface design, consistency, and exemplar alignment”
  • “/api-review”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Surface Inventory
  2. Exemplar Research
  3. Consistency Audit
  4. Documentation Governance
  5. Evidence Log

What it can do on your machine

Read from SKILL.md and the folder at commit 9f3eb00. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

API Review loads about 1.3k tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 542 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~39
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from athola/claude-night-market at commit 9f3eb00, republished under its MIT licence (© athola). 542 words, ~1,303 tokens.

Download SKILL.mdSave it as .claude/skills/api-review/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
api-review
description
Evaluates API surface design, consistency, and exemplar alignment. Use when reviewing public API changes or before releasing a new API surface.
role
library
alwaysApply
false
category
code-review
tags
api, design, consistency, documentation, versioning
usage_patterns
api-design-review, consistency-audit, documentation-governance
complexity
intermediate
model_hint
standard
estimated_tokens
400
progressive_loading
true
dependencies
imbue:proof-of-work, imbue:review-core, imbue:structured-output

API Review Workflow

When NOT To Use

  • Internal refactors behind a stable surface (use pensive:code-refinement)
  • Coupling and layering questions (use pensive:architecture-review)

Usage

Use this skill to review public API changes, design new surfaces, audit consistency, and validate documentation completeness. Run it before any API release to confirm alignment with project guidelines.

Required Progress Tracking

  1. api-review:surface-inventory
  2. api-review:exemplar-research
  3. api-review:consistency-audit
  4. api-review:docs-governance
  5. api-review:evidence-log
  6. api-review:findings-verified

Workflow

Step 1: Surface Inventory

Catalog all public APIs by language. Record stability levels, feature flags, and versioning metadata. Use tools like rg to find public symbols (e.g., pub in Rust or non-underscored def in Python). Confirm the working tree state with git status before starting.

Step 2: Exemplar Research

Identify at least two high-quality API references for the relevant language, such as pandas, requests, or tokio. Document their patterns for namespacing, pagination, error handling, and structure to serve as a baseline for the audit.

Step 3: Consistency Audit

Compare the project's API against the identified exemplar patterns. Analyze naming conventions, parameter ordering, return types, and error semantics. Identify duplication, leaky abstractions, missing feature gates, and documentation gaps.

Step 4: Documentation Governance

Validate that documentation includes entry points, quickstarts, and a complete API reference. Verify that changelogs and migration notes are maintained. Check for SemVer compliance, stability promises, and clear deprecation timelines. Confirm that documentation is generated automatically using tools like rustdoc, Sphinx, or OpenAPI.

Step 5: Evidence Log

Record all executed commands and findings. Summarize the final recommendation as Approve, Approve with actions, or Block. Include specific action items with assigned owners and due dates.

API Quality Checklist

Naming

Confirm consistent conventions and descriptive names that follow language-specific idioms.

Parameters

Verify consistent ordering and ensure optional parameters have explicit defaults. Check that type annotations are complete.

Return Values

Analyze return patterns for consistency. Confirm that error cases are documented and that pagination follows a uniform structure.

Documentation

Verify that all public APIs include usage examples and that the changelog reflects current changes.

Show full SKILL.md (213 more words)Show less

Output Format

The final report must include a summary of the API surface, a numerical inventory of endpoints and public types, and an alignment analysis against researched exemplars. Document consistency issues and documentation gaps with precise file and line references. Conclude with a clear decision and a timed action plan.

Each issue must follow this structure:

text
[A1] Title
- Location: file.py:42
- Anchor: `verbatim source text at line 42`
- Issue: what is wrong | Fix: remediation | Evidence: [E1]

The Anchor is the exact source text at Location; it is what citation_verifier.py re-reads to prove the finding is real.

Technical Integration

Use imbue:proof-of-work for reproducible command capture and imbue:structured-output for formatting findings. Reference imbue:diff-analysis/modules/risk-assessment-framework when assessing breaking changes.

Module Reference

  • See modules/surface-inventory.md for API cataloging patterns
  • See modules/exemplar-research.md for researching API standards
  • See modules/consistency-audit.md for cross-API consistency checks
Verify Findings Are Grounded (api-review:findings-verified)

Write findings to .review/findings.json, run the citation verifier (Skill(imbue:review-core) Step 5), and drop or label UNVERIFIED any the verifier rejects.

Exit Criteria

  • Surface inventoried, exemplars researched, consistency audited, documentation governance checked, and evidence logged.
  • Every reported finding carries a Location + verbatim Anchor confirmed by citation_verifier.py (exit 0), or unverified findings were dropped or labeled UNVERIFIED.

Troubleshooting

If the audit command is missing, verify that dependencies are installed and accessible in the system PATH. Check file permissions if access errors occur. Use the --verbose flag to inspect execution logs if the tool behaves unexpectedly.

© athola, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files in plugins/pensive/skills/api-review of athola/claude-night-market.

  • SKILL.md
  • modules/consistency-audit.md
  • modules/exemplar-research.md
  • modules/surface-inventory.md

Open the folder on GitHubat commit 9f3eb00

Compare with similar skills

API Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

API Review compared with similar skills
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API Review this skillathola/claude-night-market342—~1.3kAutomated safety check: PassMIT
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PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT

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Categories

Questions about API Review

What does API Review do?

Evaluates API surface design, consistency, and exemplar alignment. API Review is an agent skill from athola/claude-night-market. Evaluates API surface design, consistency, and exemplar alignment.

When should I use API Review?

API Review fits situations like: reviewing public API changes; before releasing a new API surface.

How do I install API Review in Claude Code?

Run `npx skills add athola/claude-night-market --skill api-review -a claude-code`. Or copy the skill folder (plugins/pensive/skills/api-review in athola/claude-night-market) into .claude/skills/api-review in your project. Claude Code loads it when a task matches its description.

How do I install API Review in Codex?

Run `npx skills add athola/claude-night-market --skill api-review -a codex`. Or copy the skill folder (plugins/pensive/skills/api-review in athola/claude-night-market) into .agents/skills/api-review in your project. Codex loads it when a task matches its description.

Can I use API Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add athola/claude-night-market --skill api-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/api-review, .gemini/skills/api-review, .github/skills/api-review and .opencode/skills/api-review in your project.

What does API Review need to run?

Going by SKILL.md and its folder, API Review needs the command-line tools its instructions call (git).

Does API Review access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is API Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does API Review use?

API Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does API Review use?

About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to API Review?

Skills that share tags, products or a category with API Review: Vercel Composition Patterns (supabase/supabase, 111k stars), Finishing a Development Branch (obra/superpowers, 296k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars) and PR Babysitter (openinterpreter/openinterpreter, 69k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains API Review?

athola (a GitHub user) maintains it in athola/claude-night-market, which has 342 GitHub stars. The repository holds 159 skills in this directory. The repository was last updated on October 6, 2026.

Source: athola/claude-night-market on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.