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codex-learning

Codex CLI learning and optimization guide. Teaches configuration, AGENTS.md setup, MCP servers, skills management, and best practices. Start learning with "learn codex" or "setup codex". Triggers: learn codex, codex setup, AGENTS.md, MCP, skills, configuration, 코덱스 배우기, 설정 방법, コーデックス学習, 学习Codex, aprender codex, apprendre codex, Codex lernen, imparare codex Do NOT use for: bkit-specific PDCA workflow (use $pdca).

Informações da origem

Repositório
ww-w-ai/bkit-codex
Última atividade na origem
14 de fevereiro de 2026 às 15:39
Idioma detectado do SKILL.md
inglês
Estrelas
71
Forks
23

Opções de instalação

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Leia o SKILL.md e os arquivos complementares exibidos pelo SkillsMP antes de decidir se vai instalar.

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Exibindo SKILL.md

SKILL.md
Instruções da origem · Visualização somente leitura
name
codex-learning
description
Codex CLI learning and optimization guide. Teaches configuration, AGENTS.md setup, MCP servers, skills management, and best practices. Start learning with "learn codex" or "setup codex". Triggers: learn codex, codex setup, AGENTS.md, MCP, skills, configuration, 코덱스 배우기, 설정 방법, コーデックス学習, 学习Codex, aprender codex, apprendre codex, Codex lernen, imparare codex Do NOT use for: bkit-specific PDCA workflow (use $pdca).
# Codex Learning Skill > Learn to configure and optimize OpenAI Codex CLI for maximum productivity. ## Actions | Action | Description | Example | |--------|-------------|---------| | `learn` | Start learning guide | `$codex-learning learn` | | `setup` | Configuration walkthrough | `$codex-learning setup` | | `tips` | Best practices and tips | `$codex-learning tips` | ## 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 ```bash npm install -g @openai/codex ``` ### 2. Configuration ```bash # 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: ```markdown # 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 ```json // ~/.codex/mcp.json { "servers": { "bkit-codex": { "command": "npx", "args": ["bkit-codex-mcp"], "description": "bkit development pipeline tools" } } } ``` ### Project-level MCP ```json // .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 ```yaml --- 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 ```yaml interface: brand_color: "#3B82F6" policy: allow_implicit_invocation: true ``` ## Approval Modes | Mode | Description | Best For | |------|------------|---------| | `suggest` | Shows changes, asks before applying | Learning, careful work | | `auto-edit` | Auto-applies file edits, asks for commands | Experienced users | | `full-auto` | Auto-applies everything | Trusted workflows | ## 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.
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