templates/.claude/skills/codex-exec/SKILL.md
Execute OpenAI Codex CLI prompts and return results
npx skillsauth add baekenough/oh-my-customcode codex-execInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Execute OpenAI Codex CLI prompts in non-interactive mode and return structured results. Enables Claude + Codex hybrid workflows.
<prompt> Required. The prompt to send to Codex CLI
--json Return structured JSON Lines output
--output <path> Save final message to file
--model <name> Model override (default: Codex CLI default model)
--timeout <ms> Execution timeout (default: 120000, max: 600000)
--full-auto Enable auto-approval mode (codex -a full-auto)
--working-dir Working directory for Codex execution
--effort <level> Set reasoning effort level (minimal, low, medium, high, xhigh)
Maps to Codex CLI's model_reasoning_effort config
Default: uses Codex CLI's configured default
Recommended: xhigh for research/analysis tasks
1. Pre-checks
- Verify `codex` binary is installed (which codex || npx codex --version)
- Verify authentication (OPENAI_API_KEY or logged in)
2. Build command
- Base: codex exec --ephemeral "<prompt>"
- Apply options: --json, --model, --full-auto, -C <dir>
- Set --working-dir if specified
3. Execute
- Run via Bash tool with timeout (default 2min, max 10min)
- Or use helper script: node .claude/skills/codex-exec/scripts/codex-wrapper.cjs
4. Parse output
- Text mode: return raw stdout
- JSON mode: parse JSON Lines, extract final assistant message
5. Report results
- Format output with execution metadata
--ephemeral: No session persistence (conversations not saved)--full-auto only when explicitly requested[Codex Exec] Completed
Model: (default)
Duration: 23.4s
Working Dir: /path/to/project
--- Output ---
{codex response text}
[Codex Exec] Completed (JSON)
Model: (default)
Duration: 23.4s
Events: 12
--- Final Message ---
{extracted final assistant message}
[Codex Exec] Failed
Error: {error_message}
Exit Code: {code}
Suggested Fix: {suggestion}
For complex executions, use the wrapper script:
node .claude/skills/codex-exec/scripts/codex-wrapper.cjs --prompt "your prompt" [options]
The wrapper provides:
# Simple text prompt
codex-exec "explain what this project does"
# JSON output with model override
codex-exec "list all TODO items" --json
# Save output to file
codex-exec "generate a README" --output ./README.md
# Full auto mode with custom timeout
codex-exec "fix the failing tests" --full-auto --timeout 300000
# Specify working directory
codex-exec "analyze the codebase" --working-dir /path/to/project
Works with the orchestrator pattern:
codex-exec requires the Codex CLI binary to be installed and authenticated. The skill is only usable when:
codex binary is found in PATH (which codex succeeds)codex logged in)If either check fails, this skill cannot be used. Fall back to Claude agents for the task.
Note: This skill is invoked via
/codex-execcommand, delegated by the orchestrator, or suggested by routing skills when codex is available. The intent-detection system can trigger it for research (xhigh) and code generation (hybrid) workflows.
When used within Agent Teams (requires explicit invocation):
Orchestrator delegates generation task
→ /codex-exec invoked explicitly
→ Output returned to orchestrator
→ Reviewer validates quality
→ Iterate if needed
When the orchestrator or intent-detection detects a research/information gathering request (routing_rule in agent-triggers.yaml):
codex binary and OPENAI_API_KEY/codex-exec "Research and analyze: {topic}. Provide structured findings with sources." --effort xhigh --full-auto --json
| Level | Use Case | Speed | Depth | |-------|----------|-------|-------| | minimal | Quick lookups | Fastest | Surface | | low | Simple queries | Fast | Basic | | medium | General tasks | Balanced | Standard | | high | Complex analysis | Slower | Deep | | xhigh | Research & investigation | Slowest | Maximum |
When routing skills detect a code generation task and codex is available:
/tmp/.claude-env-status-*/codex-exec "Generate {description} following {framework} best practices" --effort high --full-auto
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