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name: codex description: Invoke OpenAI Codex CLI for second opinions, multi-model analysis, architectural validation, or structured JSON output. Use when you need external AI perspective from OpenAI models to validate your decisions or get comparative analysis.

Codex Second Opinion Skill

This skill enables you to leverage OpenAI Codex CLI as a second opinion source for code analysis, architectural validation, and technical reviews.

When to Use This Skill

Invoke this skill when you need to:

• Get second opinion on architectural decisions or implementation approaches
• Multi-model validation - compare OpenAI vs Anthropic perspectives
• Code review from different AI model for better coverage
• Structured JSON output with schemas for predictable parsing
• Complex analysis that benefits from consensus of multiple AI models

Do NOT use for:

• Simple tasks that don't need validation
• Time-sensitive operations where single perspective is sufficient
• Tasks already completed and validated

How This Skill Works

When invoked, use codex exec via Bash tool with these patterns:

Pattern 1: Simple Question-Answer

codex exec --output-last-message /tmp/claude/codex-answer.txt "Your question"
cat /tmp/claude/codex-answer.txt

Pattern 2: Structured Analysis (Recommended)

# Create schema
cat > /tmp/claude/schema.json << 'EOF'
{
  "type": "object",
  "properties": {
    "summary": { "type": "string" },
    "strengths": { "type": "array", "items": { "type": "string" } },
    "weaknesses": { "type": "array", "items": { "type": "string" } },
    "recommendations": { "type": "array", "items": { "type": "string" } }
  },
  "required": ["summary", "strengths", "weaknesses"]
}
EOF

# Execute with schema
codex exec --output-schema /tmp/claude/schema.json \
  --output-last-message /tmp/claude/result.json \
  "Analyze [topic]. Provide structured assessment."

# Read result
cat /tmp/claude/result.json

Pattern 3: Comparative Analysis

# Get Codex perspective
codex exec --output-last-message /tmp/claude/codex-view.txt \
  "Review this approach: [your plan]. List pros, cons, alternatives."

# Present both perspectives
cat /tmp/claude/codex-view.txt

Common Use Cases

1. Architecture Review

cat > /tmp/claude/arch-schema.json << 'EOF'
{
  "type": "object",
  "properties": {
    "assessment": { "type": "string" },
    "risks": { "type": "array", "items": { "type": "string" } },
    "alternatives": { "type": "array", "items": { "type": "string" } },
    "risk_level": { "type": "string", "enum": ["low", "medium", "high"] }
  }
}
EOF

codex exec --output-schema /tmp/claude/arch-schema.json \
  --output-last-message /tmp/claude/arch-review.json \
  "Review MCP CLI bridge pattern. Assess security, performance, maintainability."

cat /tmp/claude/arch-review.json

2. Security Review

codex exec -m gpt-5-codex --output-last-message /tmp/claude/security.txt \
  "Security review of osiris/mcp/server.py:
   - Input validation
   - Secret handling
   - Filesystem access
   Provide specific vulnerabilities and fixes."

cat /tmp/claude/security.txt

3. Code Review

codex exec --output-last-message /tmp/claude/review.txt \
  "Review osiris/mcp/tools/discovery.py focusing on:
   1. Security vulnerabilities
   2. Performance issues
   3. Code maintainability
   Provide line-level recommendations."

cat /tmp/claude/review.txt

4. Validate ADR

codex exec --output-last-message /tmp/claude/adr-review.txt \
  "Review this ADR for completeness and issues: [ADR content or file reference]"

cat /tmp/claude/adr-review.txt

Key Parameters

• Model selection: -m gpt-5-codex (for complex tasks) or -m o4-mini (faster)
• Working directory: -C /path/to/analyze (defaults to current)
• Sandbox mode: --sandbox read-only (default, safe)
• Output: --output-last-message /tmp/claude/file.txt (cleanest for text)

Best Practices

1. Always use /tmp/claude/ for outputs - respects filesystem contract
2. Prefer JSON schemas for structured, parseable responses
3. Be specific in prompts - mention file paths, exact concerns, context
4. Compare perspectives - present both Codex and your analysis
5. Use for validation - Codex complements, doesn't replace your work
6. Check authentication - ensure codex --version works before use

Output Interpretation

When presenting Codex results to user:

1. Label clearly - "Codex perspective" or "Second opinion from OpenAI"
2. Compare with your own analysis
3. Synthesize insights from both models
4. Highlight agreement and disagreement
5. Recommend based on multi-model consensus

Error Handling

Always verify Codex is available:

if ! command -v codex &> /dev/null; then
    echo "Codex CLI not found. User needs to install Codex."
    exit 1
fi

If authentication fails, inform user to run:

codex login  # ChatGPT login
# OR
printenv OPENAI_API_KEY | codex login --with-api-key

Limitations

• Codex uses OpenAI models (GPT-5, O4), not Claude
• Requires internet connection
• Different context limits than Claude
• May have different coding style/perspective

Quick Reference

# Simple question
codex exec --output-last-message /tmp/claude/out.txt "analyze X"

# Structured output
codex exec --output-schema schema.json -o /tmp/claude/result.json "analyze X"

# Different model
codex exec -m gpt-5-codex --output-last-message /tmp/claude/out.txt "complex task"

# With image
codex exec -i screenshot.png --output-last-message /tmp/claude/out.txt "explain this"

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See reference.md for comprehensive Codex CLI documentation and advanced usage patterns.