codex-cli-delegation

name	codex-cli-delegation
description	Delegate complex code analysis, refactoring, and editing tasks to OpenAI Codex CLI from within Claude Code
triggers	["use codex to analyze this code","delegate this to codex","run codex on this repository","ask codex to refactor this","start a codex session","execute this with codex","use codex for code review","invoke codex cli"]

Codex CLI Delegation

Skill by ara.so — Codex Skills collection.

Overview

The Codex CLI (codex) is a command-line tool that enables automated code analysis, refactoring, editing, and agentic workflows using OpenAI's GPT models with specialized code-understanding capabilities. This skill enables AI coding agents to delegate tasks to Codex for multi-file operations, complex refactoring, and autonomous code editing.

Key capabilities:

• Execute one-off prompts with codex exec
• Resume interactive sessions with context persistence
• Multi-file code analysis and editing
• Automated git integration and safety checks
• Configurable sandbox modes (read-only, edit, full)
• Model selection and reasoning effort tuning

Prerequisites

Verify Codex is installed and configured:

codex --version

If not installed, follow Codex installation instructions and configure credentials:

# Set OpenAI API key
export OPENAI_API_KEY="${OPENAI_API_KEY}"

# Verify configuration
codex config show

Installation

This skill is typically installed via Claude Code's plugin system:

/plugin marketplace add skills-directory/skill-codex
/plugin install skill-codex@skill-codex

Or as a standalone skill:

git clone --depth 1 [e-mail]:skills-directory/skill-codex.git /tmp/skills-temp && \
mkdir -p ~/.claude/skills && \
cp -r /tmp/skills-temp/plugins/skill-codex/skills/codex ~/.claude/skills/codex && \
rm -rf /tmp/skills-temp

Core Commands

codex exec

Execute a one-off prompt with full configuration control:

# Basic execution
codex exec "Analyze error handling patterns in this codebase"

# With model selection
codex exec -m gpt-5.3-codex-spark "Refactor authentication module"

# With reasoning effort
codex exec --config model_reasoning_effort="high" "Find performance bottlenecks"

# With sandbox mode
codex exec --sandbox read-only "Review code quality"
codex exec --sandbox edit "Add type hints to Python files"
codex exec --sandbox full "Refactor and run tests"

# Full automation mode
codex exec --full-auto --skip-git-repo-check "Analyze this repository"

# Suppress thinking tokens (recommended for Claude Code context)
codex exec "Your prompt" 2>/dev/null

Session Resume

Continue previous Codex sessions with context:

# List available sessions
codex sessions list

# Resume a specific session
codex resume <session-id>

# Resume with additional prompt
codex resume <session-id> "Continue with the refactoring we discussed"

Model Selection

Choose the appropriate model for your task:

Model	Best For	Reasoning
gpt-5.5	Most complex tasks, architectural decisions	Highest
gpt-5.4	Advanced refactoring, multi-file analysis	High
gpt-5.4-mini	Faster analysis, simpler edits	Medium
gpt-5.3-codex-spark	Quick code review, rapid prototyping	Low-Medium
gpt-5.3-codex	Standard code operations	Low

Example:

# For complex architectural analysis
codex exec -m gpt-5.5 --config model_reasoning_effort="high" \
  "Design a plugin system for this application"

# For quick code review
codex exec -m gpt-5.3-codex-spark --config model_reasoning_effort="low" \
  "Check for security issues in authentication"

Reasoning Effort Levels

Control computational depth:

• low: Fast, surface-level analysis
• medium: Balanced speed and depth
• high: Deep reasoning, comprehensive analysis

codex exec --config model_reasoning_effort="high" \
  "Analyze concurrency patterns and race conditions"

Sandbox Modes

Control Codex's file system access:

• read-only: Analysis only, no modifications
• edit: Can modify files but limited execution
• full: Full file system and execution access

# Safe analysis
codex exec --sandbox read-only "Audit this codebase"

# Controlled editing
codex exec --sandbox edit "Add error handling to all API calls"

# Full automation (use with caution)
codex exec --sandbox full --full-auto "Implement feature X with tests"

Common Workflows

Code Analysis

# Comprehensive repository analysis
codex exec -m gpt-5.4 \
  --config model_reasoning_effort="high" \
  --sandbox read-only \
  --full-auto \
  "Analyze this repository comprehensively: architecture, patterns, code quality, potential improvements" \
  2>/dev/null

# Security audit
codex exec -m gpt-5.5 \
  --config model_reasoning_effort="high" \
  --sandbox read-only \
  "Perform security audit focusing on authentication, authorization, and data validation" \
  2>/dev/null

Refactoring

# Extract reusable components
codex exec -m gpt-5.4 \
  --sandbox edit \
  "Identify duplicated code and extract into reusable functions" \
  2>/dev/null

# Type safety improvements
codex exec -m gpt-5.3-codex-spark \
  --sandbox edit \
  "Add TypeScript type annotations to all exported functions" \
  2>/dev/null

Feature Implementation

# Implement with tests
codex exec -m gpt-5.5 \
  --config model_reasoning_effort="high" \
  --sandbox full \
  --full-auto \
  "Implement user authentication with JWT tokens, including unit tests and integration tests" \
  2>/dev/null

Documentation

# Generate comprehensive docs
codex exec -m gpt-5.4 \
  --sandbox edit \
  "Add JSDoc comments to all public APIs and update README with usage examples" \
  2>/dev/null

Configuration

Environment Variables

# OpenAI API key (required)
export OPENAI_API_KEY="${OPENAI_API_KEY}"

# Codex configuration directory (optional)
export CODEX_CONFIG_DIR="${HOME}/.config/codex"

Global Config File

Located at ~/.config/codex/config.yaml:

default_model: gpt-5.4
default_reasoning_effort: medium
default_sandbox: edit
auto_git_check: true
thinking_tokens: false

Per-Execution Config

# Override config for single execution
codex exec \
  --config model_reasoning_effort="high" \
  --config auto_git_check="false" \
  "Your prompt here"

Thinking Tokens

By default, this skill suppresses Codex's reasoning output (stderr) to avoid bloating context:

# Suppressed (default for Claude Code)
codex exec "Analyze code" 2>/dev/null

# Show thinking tokens for debugging
codex exec "Analyze code"

When to show thinking tokens:

• Debugging Codex behavior
• Understanding complex analysis decisions
• Learning from Codex's reasoning process

Safety and Git Integration

Codex includes built-in safety checks:

# Requires clean git state (recommended)
codex exec --sandbox edit "Refactor module"

# Skip git check (use with caution)
codex exec --sandbox edit --skip-git-repo-check "Quick fix"

# Full automation without prompts
codex exec --full-auto --skip-git-repo-check "Automated task"

Best practices:

1. Always work in a git repository with committed changes
2. Use read-only sandbox for analysis
3. Review changes before committing
4. Use --full-auto only for well-defined, low-risk tasks

Error Handling

Common Issues

API Key Not Set:

Error: OPENAI_API_KEY not found

Solution:

export OPENAI_API_KEY="${OPENAI_API_KEY}"

Codex Not Found:

codex: command not found

Solution: Install Codex CLI and ensure it's in PATH

Git Repository Required:

Error: Not a git repository

Solution: Initialize git or use --skip-git-repo-check

Rate Limiting:

Error: Rate limit exceeded

Solution: Reduce reasoning effort or switch to a faster model

Integration with Claude Code

When delegating to Codex from Claude Code:

1. Ask for clarification on model and reasoning effort if not specified
2. Default to read-only sandbox for analysis tasks
3. Suppress thinking tokens unless explicitly requested: 2>/dev/null
4. Summarize Codex output rather than showing raw responses
5. Offer follow-up actions based on Codex results

Example integration pattern:

# In Claude Code skill activation
def invoke_codex(prompt, model=None, reasoning=None, sandbox="read-only"):
    # Confirm model selection
    if model is None:
        # Ask user: "Which model? gpt-5.5, gpt-5.4, gpt-5.4-mini, gpt-5.3-codex-spark, gpt-5.3-codex"
        model = get_user_choice()
    
    # Confirm reasoning effort
    if reasoning is None:
        # Ask user: "Reasoning effort? low, medium, high"
        reasoning = get_user_choice()
    
    # Build command
    cmd = f'codex exec -m {model} --config model_reasoning_effort="{reasoning}" --sandbox {sandbox} --full-auto --skip-git-repo-check "{prompt}" 2>/dev/null'
    
    # Execute and return results
    return execute_command(cmd)

Advanced Patterns

Iterative Refinement

# Initial analysis
codex exec -m gpt-5.4 "Analyze authentication module" > analysis.txt

# Resume with refinements
SESSION_ID=$(codex sessions list | head -1 | awk '{print $1}')
codex resume $SESSION_ID "Focus on OAuth2 implementation details"

Multi-Stage Workflows

# Stage 1: Analysis (read-only)
codex exec --sandbox read-only \
  "Identify components that need refactoring" > refactor-plan.txt

# Stage 2: Refactoring (edit)
codex exec --sandbox edit \
  "Refactor components listed in refactor-plan.txt"

# Stage 3: Testing (full)
codex exec --sandbox full \
  "Run test suite and fix any failures"

Combining with Shell Scripts

#!/bin/bash
# automated-review.sh

echo "Starting Codex code review..."

# Security audit
codex exec -m gpt-5.5 \
  --config model_reasoning_effort="high" \
  --sandbox read-only \
  "Security audit focusing on OWASP Top 10" \
  2>/dev/null > security-report.md

# Code quality
codex exec -m gpt-5.4 \
  --sandbox read-only \
  "Code quality analysis: complexity, maintainability, test coverage" \
  2>/dev/null > quality-report.md

echo "Reports generated: security-report.md, quality-report.md"

Troubleshooting

Performance Issues

If Codex is slow:

• Use lower reasoning effort: --config model_reasoning_effort="low"
• Switch to faster model: -m gpt-5.3-codex-spark
• Narrow the scope of your prompt

Context Window Limits

If hitting context limits:

• Break large tasks into smaller prompts
• Use --sandbox read-only to limit file scanning
• Exclude large dependencies or build artifacts

Inconsistent Results

If results vary significantly:

• Increase reasoning effort for more consistent analysis
• Use gpt-5.5 or gpt-5.4 for complex tasks
• Provide more specific, detailed prompts

Resources

• Codex CLI Documentation
• Model Comparison Guide
• Agentic Workflows with ralph-meets-rex