log-virality-issues
Run /check-virality, then create GitHub issues for all findings. Issues are created with priority labels and structured format. Use /fix-virality instead if you want to fix issues immediately.
SKILL.md
| Name | log-virality-issues |
| Description | Run /check-virality, then create GitHub issues for all findings. Issues are created with priority labels and structured format. Use /fix-virality instead if you want to fix issues immediately. |
Codex CLI Configuration
OpenAI Codex CLI setup with skills, workflows, and profiles ported from Claude Code.
Quick Start
# Use a profile
codex --profile ultrathink "review this architecture"
codex --profile execute "implement next task"
codex --profile ship "complete feature workflow"
# Use skills (explicit invocation)
codex "Use ship skill"
codex "Use execute skill"
codex "Use ultrathink skill"
Repository Layout
config/– Canonical CLI configuration (config.toml,config.json) plus MCP blocksskills/– Skill library (skills/<name>/SKILL.md)rules/– Command allow/deny rulesscripts/– Operational tooling (doctor,lint-config,check-skills,check-mcp-exa)secrets/– Non-committed env stubs (copyexa.env.example→exa.env, export before use)docs/CHANGELOG.md– Versioned history for repo changesagents/– Persona instructions for reviews
Profiles
Configured in config/config.toml, profiles switch between different model and approval settings.
ultrathink - Deep Architectural Review
- Model: GPT-5
- Reasoning: High
- Approval: Never
- Use for: Design critique, complexity analysis, architecture decisions
execute - Tactical Implementation
- Model: GPT-5-Codex
- Reasoning: Medium
- Approval: Never
- Use for: Task execution, feature implementation, coding work
ship - Complete Workflows
- Model: GPT-5-Codex
- Reasoning: High
- Approval: Never
- Use for: End-to-end feature delivery, spec → implementation → PR
fast - Quick Tasks
- Model: GPT-5
- Reasoning: Low
- Approval: Never
- Use for: Quick edits, simple refactors, minor fixes
Skills
Skills replace prompts. Each skill lives in skills/<name>/SKILL.md with frontmatter metadata.
Invocation:
- Explicit: mention the skill name, e.g., “Use
shipskill” - Implicit: describe the task; the agent will pick matching skills
Example Workflows
Complete Feature Development
# High-reasoning full workflow
codex --profile ship "Use ship skill"
# Or step-by-step:
codex "Use prime skill" # Recon project state and conventions
codex "Use spec skill" # Produce the PRD with alternatives
codex "Use plan skill" # Build issue task list
codex "Use flesh skill" # Clarify vague tasks
codex "Use execute skill" # Implement the next task
codex "Use debug skill" # Optional: bug hunts
codex "Use qa-cycle skill" # Test and fix
codex "Use pr skill" # Draft PR title + body
codex "Use code-review skill" # Brutal self-review
codex "Use pr-ready skill" # Final quality gate
Design Review
codex --profile ultrathink "Use ultrathink skill"
Task Execution
codex --profile execute "Use execute skill"
Code Review
codex "Use ousterhout skill"
codex "Use testing skill"
Shell Aliases
Add to your ~/.zshrc or ~/.bashrc:
# Codex with profiles
alias cdx='codex'
alias cdx-think='codex --profile ultrathink'
alias cdx-exec='codex --profile execute'
alias cdx-ship='codex --profile ship'
alias cdx-fast='codex --profile fast'
# Common skills
alias cdx-ultra='codex "Use ultrathink skill"'
alias cdx-arch='codex "Use architect skill"'
alias cdx-prime='codex "Use prime skill"'
alias cdx-spec='codex "Use spec skill"'
alias cdx-plan='codex "Use plan skill"'
alias cdx-do='codex "Use execute skill"'
alias cdx-qa='codex "Use qa-cycle skill"'
alias cdx-ready='codex "Use pr-ready skill"'
alias cdx-debug='codex "Use debug skill"'
alias cdx-pr='codex "Use pr skill"'
alias cdx-review='codex "Use code-review skill"'
alias cdx-respond='codex "Use git-respond skill"'
alias cdx-ci='codex "Use ci skill"'
Then reload: source ~/.zshrc
EXA MCP Integration
- Copy
secrets/exa.env.example→secrets/exa.env, populateEXA_API_KEY. - Export the variable (
source secrets/exa.envor add to your shell profile). - Run
scripts/check-mcp-exa.shto confirm connectivity. - Codex consumes the key via the
[mcp.exa]block inconfig/config.tomlorconfig/config.json.
Operational Scripts
scripts/doctor.sh # One-stop health check (git, config, skills, MCP)
scripts/lint-config.sh # Validates JSON/TOML
scripts/check-skills.sh # Ensures SKILL frontmatter exists
scripts/check-mcp-exa.sh # Lightweight EXA MCP ping (requires EXA_API_KEY)
Integrate scripts/doctor.sh into your pre-flight routine before large edits.
Configuration Files
config/config.toml- Main configuration with profiles, project trust levels, and MCP settingsconfig/config.json- Provider registry mirrored for CodexAGENTS.md- Core philosophy and design principlesskills/- Skill library organized by namerules/- Command allow/deny rules
Philosophy
This configuration mirrors the Claude Code workflow system, bringing:
- Complexity Management - Ousterhout principles baked into every workflow
- Quality Gates - Automated validation before PR creation
- Workflow Orchestration - Guided processes from spec to shipped feature
- Profile-Based Context - Switch between deep thinking and fast execution
Customization
Adding New Skills
Create skills/<name>/SKILL.md:
---
name: my-skill
description: What this skill does
aliases: [short-name]
enabled: true
---
# My Skill
Prompt content here...
Invoke with: codex "Use my-skill skill"
Adding New Profiles
Edit config/config.toml:
[profiles.myprofile]
model = "gpt-5-codex"
model_reasoning_effort = "medium"
approval_policy = "never"
sandbox_mode = "workspace-write"