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codex-review

Professional code review with auto CHANGELOG generation, integrated with Codex AI. Use when you want professional code review before commits, you need automatic CHANGELOG generation, or reviewing large-scale refactoring.

Published by sickn33 ↗sickn33/agentic-awesome-skills

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codex-review

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Use codex-review to review [input] before it is committed and generate the corresponding CHANGELOG.md entry; identify issues that require environment-specific validation or expert review

Required inputs

  • [input]

User-approved starter prompt based on a pinned source version; check current skill requirements before running. Task evidence ↗

SKILL.md

name: codex-reviewdescription: "Professional code review with auto CHANGELOG generation, integrated with Codex AI. Use when you want professional code review before commits, you need automatic CHANGELOG generation, or reviewing large-scale refactoring."risk: criticalsource: communitydate_added: "2026-02-27"

codex-review

Overview

Professional code review with auto CHANGELOG generation, integrated with Codex AI

When to Use

  • When you want professional code review before commits
  • When you need automatic CHANGELOG generation
  • When reviewing large-scale refactoring

Installation

npx skills add -g BenedictKing/codex-review

Step-by-Step Guide

  1. This entrypoint does not bundle the upstream integration. Inspect a selected upstream revision and authorize installation scope before using the installation option above.
  2. Ensure Codex CLI is installed
  3. Use /codex-review only when the installed host exposes it. Pin repository/base/head and inspect the net diff directly; return findings with exact trigger, location and evidence. A generated CHANGELOG must match the actual diff and must not rewrite unrelated release history.

Examples

See GitHub Repository for examples.

Best Practices

  • Keep CHANGELOG.md in your project root
  • Use conventional commit messages

Troubleshooting

See the GitHub repository for troubleshooting guides.

Related Skills

  • context7-auto-research, tavily-web, exa-search, firecrawl-scraper

Limitations

  • An automated reviewer is advisory, not merge approval. Confirm provider/data/cost scope before sending private source externally; no implicit commit, push or publication.
  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.