letitbk/cursor-setup/codex

Claude Code and agent skill by letitbk/cursor-setup

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Get code reviews and second opinions using OpenAI Codex CLI (GPT-5.3). Use for reviewing code changes, getting alternative perspectives on implementations, or validating approaches with another AI model.

Install

npx vskill@latest install letitbk/cursor-setup/codex

SKILL.md

Codex Review & Second Opinion Skill

Use OpenAI's Codex CLI to get code reviews and second opinions. This provides an independent AI perspective using GPT-5.3 or o3 models.

When to Use This Skill

Trigger when user:

  • Uses /codex command explicitly
  • Asks for a "code review"
  • Wants a "second opinion" on code or approach
  • Says "review this", "check this code", "validate this"
  • Asks "what do you think about this implementation"
  • Wants to "double check" code changes
  • Requests "another perspective" on code

Prerequisites

Codex CLI must be installed and authenticated:

bash
# Check installation
which codex
# Login if needed
codex login

Workflow

Step 1: Determine What to Review

ALWAYS ask the user what they want reviewed:

Use AskUserQuestion to clarify:

  1. Scope: What should be reviewed?
  • Uncommitted changes (staged/unstaged)
  • Specific file(s)
  • Changes against a branch
  • A specific commit
  • General approach/implementation question
  1. Model: Which model to use?
  • gpt-5.3-codex - Fast, good quality (default)
Step 2: Execute Review

IMPORTANT: Always use `--full-auto` to avoid confirmation prompts.

Mode 1: Review Uncommitted Changes
bash
codex review --full-auto --uncommitted -m MODEL "CUSTOM_INSTRUCTIONS"
Mode 2: Review Against Branch
bash
codex review --full-auto --base BRANCH -m MODEL "CUSTOM_INSTRUCTIONS"
Mode 3: Review Specific Commit
bash
codex review --full-auto --commit SHA -m MODEL "CUSTOM_INSTRUCTIONS"
Mode 4: Second Opinion on Specific Files
bash
codex exec --full-auto -m MODEL "Review these files for issues, improvements, and best practices: FILE1 FILE2"
Mode 5: General Second Opinion
bash
codex exec --full-auto -m MODEL "I need a second opinion on: USER_QUESTION"
Step 3: Save Output

After review completes, save output to markdown file:

  • Location: Same directory as reviewed code or current working directory
  • Filename pattern: codex_review_YYYYMMDD_HHMMSS.md

Command Reference

Code Review Commands
bash
# Review uncommitted changes (no confirmations)
codex review --full-auto --uncommitted -m gpt-5.3-codex
# Review with custom instructions
codex review --full-auto --uncommitted -m gpt-5.3-codex "Focus on security vulnerabilities and performance"
# Review against main branch
codex review --full-auto --base main -m gpt-5.3-codex
# Review specific commit
codex review --full-auto --commit abc123 -m gpt-5.3-codex
# Review with title context
codex review --full-auto --uncommitted --title "Add user authentication" -m gpt-5.3-codex
Second Opinion Commands
bash
# Ask about specific code
codex exec --full-auto -m gpt-5.3-codex "Review this implementation approach and suggest improvements"
# Get opinion on architecture
codex exec --full-auto -m o3 "Evaluate this architecture decision: USER_CONTEXT"
# Review specific files
codex exec --full-auto -m gpt-5.3-codex -C /path/to/project "Review src/auth.py for security issues"
Output Capture
bash
# Save last message to file (preferred method)
codex exec --full-auto -m gpt-5.3-codex -o review_output.md "Review prompt here"
# Or capture full output
codex review --full-auto --uncommitted -m gpt-5.3-codex 2>&1 | tee review.md

Usage Examples

Example 1: Review Before Commit
User: Review my changes before I commit
Claude asks: What model? (gpt-5.3-codex / o3)
User: gpt-5.3-codex
Claude executes:
codex review --full-auto --uncommitted -m gpt-5.3-codex -o codex_review_20260111_140000.md
Reports: Review saved to codex_review_20260111_140000.md
Example 2: Second Opinion on Approach
User: Get a second opinion on my authentication implementation
Claude asks: Which files? What specific concerns?
User: src/auth.py - is my JWT handling secure?
Claude executes:
codex exec --full-auto -m gpt-5.3-codex -o codex_review_auth.md "Review src/auth.py focusing on JWT security. Is the implementation secure? Any vulnerabilities?"
Example 3: Compare with Main
User: Review my feature branch against main
Claude executes:
codex review --full-auto --base main -m gpt-5.3-codex -o codex_review_feature.md "Review all changes for code quality and potential bugs"

Available Models

ModelBest ForSpeed
gpt-5.3-codexGeneral reviews, quick feedbackFast
o3Deep analysis, complex reasoningSlower

AskUserQuestion Template

When triggered, ask:

Question 1: "What would you like Codex to review?"
Options:
- Uncommitted changes (git working tree)
- Changes against a branch
- Specific file(s)
- General question/second opinion
Question 2: "Which model should I use?"
Options:
- gpt-5.3-codex (faster)
- o3 (more thorough)

Output Handling

  1. Use -o filename.md to save output directly (cleaner than tee)
  2. Save to: codex_review_YYYYMMDD_HHMMSS.md in current directory
  3. Report file location to user after completion
  4. Display key findings summary

Error Handling

ErrorSolution
Not logged inRun codex login
Not in git repoUse -C /path or --skip-git-repo-check
Model not availableFall back to gpt-5.3-codex
TimeoutTry with smaller scope or faster model

Tips

  1. Be specific: Provide context about what to focus on
  2. Review incrementally: Review smaller changes more frequently
  3. Custom instructions: Add focus areas like "security", "performance", "readability"
  4. Working directory: Codex needs to be run from the project directory
  5. Always use --full-auto: Prevents interactive confirmation prompts

Limitations

  • Requires internet connection and OpenAI API access
  • Rate limits may apply
  • Large codebases may need scoped reviews
  • Cannot review files outside git repository by default

Non-Git Directories

When running outside a git repository, use --skip-git-repo-check:

bash
codex exec --full-auto --skip-git-repo-check -m gpt-5.3-codex "Your prompt here"

This is useful for:

  • Reviewing standalone scripts
  • Getting opinions on code snippets
  • General programming questions

Alternative: Codex MCP Server

For tighter integration without shell overhead, Codex can run as an MCP server. See the codex-mcp MCP server configuration for native tool integration.

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

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