sickn33/agentic-awesome-skills

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.

First seen Jan 25, 2026

Installation

$ npx skills add sickn33/agentic-awesome-skills --skill codex-review

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Also in this package

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npx skills add sickn33/agentic-awesome-skills

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 46.2K
License LICENSE
Default branch main
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents codex

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,490 B
  • docs SUMMARY.md 240 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 578 installs

SKILL.md

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. 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 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.