Codex Review
Run Codex-integrated professional code review with automatic CHANGELOG updates before you commit or after large refactors.
Install
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill codex-reviewWhat is this skill?
- Professional code review workflow integrated with Codex AI
- Automatic CHANGELOG generation tied to review output
- Natural language or /codex-review style invocation before commits
- Oriented to large-scale refactoring review passes
- Expects CHANGELOG.md at project root and conventional commits
Adoption & trust: 488 installs on skills.sh; 40.1k GitHub stars; 3/3 security scanners passed (skills.sh audits).
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Journey fit
Primary fit
Canonical shelf is Ship review because the skill is framed for pre-commit review and changelog discipline at release boundaries. Review subphase matches professional diff review and conventional-commit-aligned changelog generation before merge.
Common Questions / FAQ
Is Codex Review safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.
SKILL.md
READMESKILL.md - Codex Review
# 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 ```bash npx skills add -g BenedictKing/codex-review ``` ## Step-by-Step Guide 1. Install the skill using the command above 2. Ensure Codex CLI is installed 3. Use `/codex-review` or natural language triggers ## Examples See [GitHub Repository](https://github.com/BenedictKing/codex-review) 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 - 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.