Del Taiseiozaki Claude Code Orchestra Codex System

Codex System — Planning, Design & Complex Implementation

Codex CLI handles planning, design, and complex code implementation.

Detailed rules: .claude/rules/codex-delegation.md

Two Roles of Codex

1. Planning & Design

• Architecture design, module composition
• Implementation plan creation (step breakdown, dependency ordering)
• Trade-off evaluation, technology selection
• Code review (quality and correctness analysis)

2. Complex Implementation

• Complex algorithms, optimization
• Debugging with unknown root causes
• Advanced refactoring
• Multi-step implementation tasks

When to Consult (MUST)

When NOT to Consult

• Simple file edits, typo fixes
• Tasks that simply follow explicit user instructions
• git commit, test execution, lint
• Codebase analysis → general-purpose subagent (Opus 1M context)
• External information retrieval → general-purpose subagent (Opus, WebSearch/WebFetch)
• Multimodal processing → Gemini CLI (PDF/video/audio/images)

How to Consult

Subagent Pattern (Recommended)

Task tool parameters:
- subagent_type: "general-purpose"
- run_in_background: true (optional)
- prompt: |
    Consult Codex about: {topic}

    codex exec --model gpt-5.4 --sandbox read-only --full-auto "
    {question for Codex}
    " 2>/dev/null

    Return CONCISE summary (key recommendation + rationale).

Direct Call (responses up to ~50 lines)

codex exec --model gpt-5.4 --sandbox read-only --full-auto "Brief question" 2>/dev/null

Having Codex Implement Code

codex exec --model gpt-5.4 --sandbox workspace-write --full-auto "
Implement: {task description}
Requirements: {requirements}
Files: {file paths}
" 2>/dev/null

Sandbox Modes

Task Templates

Implementation Planning

codex exec --model gpt-5.4 --sandbox read-only --full-auto "
Create an implementation plan for: {feature}

Context: {relevant architecture/code}

Provide:
1. Step-by-step plan with dependencies
2. Files to create/modify
3. Key design decisions
4. Risks and mitigations
" 2>/dev/null

Design Review

codex exec --model gpt-5.4 --sandbox read-only --full-auto "
Review this design approach for: {feature}

Context: {relevant code or architecture}

Evaluate:
1. Is this approach sound?
2. Alternative approaches?
3. Potential issues?
4. Recommendations?
" 2>/dev/null

Debug Analysis

codex exec --model gpt-5.4 --sandbox read-only --full-auto "
Debug this issue:

Error: {error message}
Code: {relevant code}
Context: {what was happening}

Analyze root cause and suggest fixes.
" 2>/dev/null

Language Protocol

1. Ask Codex in English
2. Receive response in English
3. Execute based on advice
4. Report to user in the user's language

Codex Plugin Commands (codex-plugin-cc)

When the openai/codex-plugin-cc plugin is installed, these slash commands are available:

Code Review

/codex:review                    # Review current uncommitted changes
/codex:review --base main        # Review branch diff against main
/codex:review --background       # Run review in background

Adversarial Review

/codex:adversarial-review                           # Challenge design decisions
/codex:adversarial-review --base main               # Branch-level adversarial review
/codex:adversarial-review --background look for race conditions

Task Delegation (Rescue)

/codex:rescue investigate why the tests started failing
/codex:rescue fix the failing test with the smallest safe patch
/codex:rescue --resume apply the top fix from the last run
/codex:rescue --model gpt-5.4-mini --effort medium investigate flaky test
/codex:rescue --background investigate the regression

Job Management

/codex:status                    # Check progress of background jobs
/codex:result                    # Show finished job output
/codex:cancel                    # Cancel active background job

Setup

/codex:setup                     # Check if Codex is installed and authenticated
/codex:setup --enable-review-gate   # Enable auto-review gate (use with caution)
/codex:setup --disable-review-gate  # Disable review gate

When to Use Plugin vs Direct CLI

Why Codex?

• Deep reasoning: Complex analysis and problem-solving
• Planning expertise: Architecture and implementation strategies
• Code mastery: Complex algorithms, optimization, debugging
• Consistency: Same project context via context-loader skill

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