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Codex Review

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alinaqi
codex-review

OpenAI Codex CLI code review with GPT-5.2-Codex, CI/CD integration

Overview

Publisheralinaqi
Repositorymaggy
Skill namecodex-review
Stars
707
Forks
57
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by alinaqi on GitHub. Read the source before you install it.

Installation

Install the Codex Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/alinaqi/maggy/tree/main/skills/codex-review
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/alinaqi/maggy.git /tmp/maggy
mkdir -p .claude/skills
cp -r /tmp/maggy/skills/codex-review .claude/skills/codex-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Codex Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Codex Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Codex Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

OpenAI Codex Code Review Skill

Use OpenAI's Codex CLI for specialized code review with GPT-5.2-Codex - trained specifically for detecting bugs, security flaws, and code quality issues.

Sources: Codex CLI | GitHub | Code Review Cookbook


Why Codex for Code Review?

FeatureBenefit
GPT-5.2-CodexSpecialized training for code review
88% detection rateBugs, security flaws, style issues (LiveCodeBench)
Structured outputJSON schema for consistent findings
GitHub native@codex review in PR comments
Headless modeCI/CD automation without TUI

Installation

Prerequisites

bash
# Check Node.js version (requires 22+)
node --version

# Install Node.js 22 if needed
# macOS
brew install node@22

# Or via nvm
nvm install 22
nvm use 22

Install Codex CLI

bash
# Via npm (recommended)
npm install -g @openai/codex

# Via Homebrew (macOS)
brew install --cask codex

# Verify installation
codex --version

Authentication

Option 1: ChatGPT Subscription (Plus, Pro, Team, Edu, Enterprise)

bash
codex
# Follow prompts to sign in with ChatGPT account

Option 2: OpenAI API Key

bash
# Set environment variable
export OPENAI_API_KEY=sk-proj-...

# Or add to shell profile
echo 'export OPENAI_API_KEY=sk-proj-...' >> ~/.zshrc

# Run Codex
codex

Shell Completions (Optional)

bash
# Bash
codex completion bash >> ~/.bashrc

# Zsh
codex completion zsh >> ~/.zshrc

# Fish
codex completion fish > ~/.config/fish/completions/codex.fish

Interactive Code Review

Launch Review Mode

bash
# Start Codex
codex

# In the TUI, type:
/review

Review Presets

PresetUse Case
Review against base branchBefore opening PR - diffs against upstream
Review uncommitted changesBefore committing - staged + unstaged + untracked
Review a commitAnalyze specific SHA from history
Custom instructionse.g., "Focus on security vulnerabilities"

Example Session

$ codex
> /review

Select review type:
❯ Review against a base branch
  Review uncommitted changes
  Review a commit
  Custom review instructions

Select base branch: main

Reviewing changes...

┌─────────────────────────────────────────────────────────────┐
│ CODE REVIEW FINDINGS                                        │
├─────────────────────────────────────────────────────────────┤
│ 🔴 CRITICAL: SQL Injection vulnerability                    │
│    File: src/api/users.ts:45                                │
│    Issue: User input directly interpolated in query         │
│    Fix: Use parameterized queries                           │
├─────────────────────────────────────────────────────────────┤
│ 🟠 HIGH: Missing authentication check                       │
│    File: src/api/admin.ts:23                                │
│    Issue: Admin endpoint accessible without auth            │
│    Fix: Add requireAuth middleware                          │
├─────────────────────────────────────────────────────────────┤
│ 🟡 MEDIUM: Inefficient database query                       │
│    File: src/services/orders.ts:89                          │
│    Issue: N+1 query pattern in loop                         │
│    Fix: Use batch query or JOIN                             │
└─────────────────────────────────────────────────────────────┘

Headless Mode (Automation)

Basic Usage

bash
# Simple review
codex exec "review the code for bugs and security issues"

# Review with JSON output
codex exec --json "review uncommitted changes" > review.json

# Save final message to file
codex exec --output-last-message review.txt "review the diff against main"

Full Automation (CI/CD)

bash
# Full auto mode (use only in isolated runners!)
codex exec \
  --full-auto \
  --json \
  --output-last-message findings.txt \
  --sandbox read-only \
  -m gpt-5.2-codex \
  "Review this code for bugs, security issues, and performance problems"

Structured Output with Schema

bash
# Define output schema
cat > review-schema.json << 'EOF'
{
  "type": "object",
  "properties": {
    "findings": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "severity": { "enum": ["critical", "high", "medium", "low"] },
          "title": { "type": "string" },
          "file": { "type": "string" },
          "line": { "type": "integer" },
          "description": { "type": "string" },
          "suggestion": { "type": "string" }
        },
        "required": ["severity", "title", "file", "description"]
      }
    },
    "summary": { "type": "string" },
    "approved": { "type": "boolean" }
  },
  "required": ["findings", "summary", "approved"]
}
EOF

# Run with schema validation
codex exec \
  --output-schema review-schema.json \
  --output-last-message review.json \
  "Review the staged changes and output findings"

GitHub Integration

Option 1: PR Comment Trigger

In any pull request, add a comment:

@codex review

Codex will respond with a standard GitHub code review.

Option 2: GitHub Action

yaml
# .github/workflows/codex-review.yml
name: Codex Code Review

on:
  pull_request:
    types: [opened, synchronize]

jobs:
  review:
    runs-on: ubuntu-latest
    permissions:
      contents: read
      pull-requests: write

    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0

      - name: Codex Review
        uses: openai/codex-action@main
        with:
          openai_api_key: ${{ secrets.OPENAI_API_KEY }}
          model: gpt-5.2-codex
          safety_strategy: drop-sudo

Option 3: Manual Headless in CI

yaml
# .github/workflows/codex-review.yml
name: Codex Code Review

on:
  pull_request:

jobs:
  review:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0

      - uses: actions/setup-node@v4
        with:
          node-version: '22'

      - name: Install Codex CLI
        run: npm install -g @openai/codex

      - name: Run Review
        env:
          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
        run: |
          # Get diff
          git diff origin/${{ github.base_ref }}...HEAD > diff.txt

          # Run Codex review
          codex exec \
            --full-auto \
            --sandbox read-only \
            --output-last-message review.md \
            "Review this git diff for bugs, security issues, and code quality: $(cat diff.txt)"

      - name: Post Review Comment
        uses: actions/github-script@v7
        with:
          script: |
            const fs = require('fs');
            const review = fs.readFileSync('review.md', 'utf8');
            github.rest.issues.createComment({
              owner: context.repo.owner,
              repo: context.repo.repo,
              issue_number: context.issue.number,
              body: `## 🤖 Codex Code Review\n\n${review}`
            });

GitLab CI/CD

yaml
# .gitlab-ci.yml
codex-review:
  image: node:22
  stage: review
  script:
    - npm install -g @openai/codex
    - |
      codex exec \
        --full-auto \
        --sandbox read-only \
        --output-last-message review.md \
        "Review the merge request changes for bugs and security issues"
    - cat review.md
  artifacts:
    paths:
      - review.md
  rules:
    - if: $CI_PIPELINE_SOURCE == "merge_request_event"

Jenkins Pipeline

groovy
pipeline {
    agent any

    environment {
        OPENAI_API_KEY = credentials('openai-api-key')
    }

    stages {
        stage('Install Codex') {
            steps {
                sh 'npm install -g @openai/codex'
            }
        }

        stage('Code Review') {
            steps {
                sh '''
                    codex exec \
                      --full-auto \
                      --sandbox read-only \
                      --output-last-message review.md \
                      "Review the code changes for bugs and security issues"
                '''
            }
        }

        stage('Publish Results') {
            steps {
                archiveArtifacts artifacts: 'review.md'
                script {
                    def review = readFile('review.md')
                    echo "Code Review Results:\n${review}"
                }
            }
        }
    }
}

Configuration

Config File

toml
# ~/.codex/config.toml

[model]
default = "gpt-5.2-codex"  # Best for code review

[sandbox]
default = "read-only"  # Safe for reviews

[review]
# Custom review instructions applied to all reviews
instructions = """
Focus on:
1. Security vulnerabilities (OWASP Top 10)
2. Performance issues (N+1 queries, memory leaks)
3. Error handling gaps
4. Type safety issues
"""

Per-Project Config

toml
# .codex/config.toml (in project root)

[review]
instructions = """
This is a Python FastAPI project. Focus on:
- Async/await correctness
- Pydantic model validation
- SQL injection via SQLAlchemy
- Authentication/authorization gaps
"""

CLI Quick Reference

bash
# Interactive
codex                          # Start TUI
/review                        # Open review presets

# Headless
codex exec "prompt"            # Non-interactive execution
codex exec --json "prompt"     # JSON output
codex exec --full-auto "prompt"  # No approval prompts

# Key Flags
--output-last-message FILE     # Save response to file
--output-schema FILE           # Validate against JSON schema
--sandbox read-only            # Restrict file access
-m gpt-5.2-codex              # Use best review model
--json                         # Machine-readable output

# Resume
codex exec resume SESSION_ID   # Continue previous session

Comparison: Claude vs Codex Review

AspectClaude (Built-in)Codex CLI
SetupNone (already in Claude Code)Install CLI + auth
ModelClaudeGPT-5.2-Codex (specialized)
ContextFull conversation contextFresh context per review
IntegrationNativeGitHub, GitLab, Jenkins
OutputMarkdownJSON schema support
Best forQuick reviews, in-flowCI/CD, critical PRs

Security Considerations

CI/CD Safety

yaml
# Always use these flags in CI/CD:
--sandbox read-only           # Prevent file modifications
--safety-strategy drop-sudo   # Revoke elevated permissions

API Key Protection

yaml
# GitHub Actions - use secrets
env:
  OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}

# Never hardcode keys
# Never echo keys in logs

Public Repositories

For public repos, use drop-sudo safety strategy to prevent Codex from reading its own API key during execution.


Troubleshooting

IssueSolution
codex: command not foundRun npm install -g @openai/codex
Node.js version errorUpgrade to Node.js 22+
Authentication failedRe-run codex and sign in again
API key invalidCheck OPENAI_API_KEY env var
Timeout in CIAdd --timeout 300 flag
Rate limitedReduce frequency or upgrade plan

Anti-Patterns

  • Using --dangerously-bypass-approvals-and-sandbox casually - Only in isolated CI runners
  • Exposing API keys in logs - Use secrets management
  • Skipping sandbox in CI - Always use --sandbox read-only
  • Ignoring findings - Review and address or document exceptions
  • Running on every commit - Use on PRs only to save costs

Frequently asked questions

What does the Codex Review AI skill do?

OpenAI Codex CLI code review with GPT-5.2-Codex, CI/CD integration

Why use Codex Review on TypingMind?

Because you install it once and use it with any model. Codex Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Codex Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/alinaqi/maggy/tree/main/skills/codex-review. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Codex Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Codex Review?

As many as you like. As long as a model supports skills, you can use Codex Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Codex Review AI skill free?

Yes. It is published on GitHub by alinaqi under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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