Popup Studio AI Bkit Codex Codex Learning

Codex Learning Skill

Learn to configure and optimize OpenAI Codex CLI for maximum productivity.

Actions

What is Codex CLI?

Codex CLI is OpenAI's command-line coding agent that:

• Reads and writes files in your project
• Executes shell commands
• Uses tools via MCP (Model Context Protocol)
• Follows instructions from AGENTS.md files
• Invokes skills for specialized tasks

Quick Start

1. Installation

npm install -g @openai/codex

2. Configuration

# Create config directory
mkdir -p ~/.codex

# Create config.toml
cat > ~/.codex/config.toml << 'CONFIG'
model = "o4-mini"
approval_mode = "suggest"

[history]
persistence = "save_all"
save_to = "$HOME/.codex/history"

[sandbox]
network_access = true
CONFIG

3. Project Setup

Create AGENTS.md at your project root:

# Project Agent Instructions

## Project Overview
Brief description of this project.

## Tech Stack
- Frontend: Next.js 14, TypeScript, Tailwind CSS
- Backend: bkend.ai BaaS
- Level: Dynamic

## Conventions
- Use TypeScript strict mode
- Follow ESLint + Prettier rules
- Commit messages: conventional commits format

## File Structure
[Describe your project structure]

## Important Notes
[Project-specific instructions for the AI]

AGENTS.md Guide

Location Hierarchy

project/
├── AGENTS.md                # Root (applies to entire project)
├── src/
│   ├── AGENTS.md           # Applies to src/ and subdirectories
│   ├── components/
│   │   └── AGENTS.md       # Applies to components/
│   └── lib/
│       └── AGENTS.md       # Applies to lib/

Child AGENTS.md files inherit from parent and can add/override instructions.

Best Practices for AGENTS.md

1. Be specific: "Use TypeScript strict mode" not "write good code"
2. Include conventions: Naming rules, file structure, patterns
3. List tech stack: Framework versions, key dependencies
4. Define boundaries: What the AI should and should not do
5. Keep it updated: Review and update as project evolves

MCP Server Configuration

What is MCP?

Model Context Protocol allows Codex to connect to external tools and data sources.

Configure MCP Servers

// ~/.codex/mcp.json
{
  "servers": {
    "bkit-codex": {
      "command": "npx",
      "args": ["bkit-codex-mcp"],
      "description": "bkit development pipeline tools"
    }
  }
}

Project-level MCP

// .codex/mcp.json (in project root)
{
  "servers": {
    "project-tools": {
      "command": "node",
      "args": ["./tools/mcp-server.js"]
    }
  }
}

Skills System

What are Skills?

Skills are reusable instruction sets that Codex loads when triggered by keywords in your prompt.

Skill Structure

.agents/skills/
├── my-skill/
│   ├── SKILL.md              # Instructions (YAML frontmatter + body)
│   └── agents/
│       └── openai.yaml       # Codex-specific config

SKILL.md Format

---
name: my-skill
description: |
  Brief description of what this skill does.
  Triggers: keyword1, keyword2, keyword3
  Do NOT use for: things this skill should not handle.
---

# Skill Body

Instructions for the AI when this skill is activated.

openai.yaml Format

interface:
  brand_color: "#3B82F6"
policy:
  allow_implicit_invocation: true

Approval Modes

Best Practices

Effective Prompts

• Be specific about what you want
• Reference file paths explicitly
• Mention the framework/language
• Ask for one thing at a time for complex tasks

Project Organization

• Keep AGENTS.md up to date
• Use .codex/ for project-specific config
• Store skills in .agents/skills/
• Use MCP for tool integration

Performance Tips

• Use o4-mini for fast tasks, o3 for complex reasoning
• Break large tasks into smaller steps
• Use skills to provide context instead of repeating instructions
• Keep AGENTS.md concise (under 2000 words)

Codex CLI Reference

See references/codex-guide.md for complete command reference and advanced configuration.

Converted and distributed by TomeVault — claim your Tome and manage your conversions.