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Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/qhkm/pi-rs.
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An example skill demonstrating the SKILL.md format
原文语言：英语
仓库 README 来源：README.md
# π (pi) — AI Coding Agent [](https://www.rust-lang.org) [](LICENSE) []() > **Minimal core. Maximum extensibility. Your workflow, your way.** A high-performance, terminal-native AI coding agent built in Rust. This is a Rust port of [pi-mono](https://github.com/badlogic/pi-mono), originally created by [Mario Zechner](https://github.com/badlogic). Features 101+ LLM models across 17 cloud providers, advanced TUI with streaming responses, and extensible plugin architecture. **Philosophy:** Pi provides primitives, not features. Sub-agents, plan mode, permission gates—build them yourself or install a package. Adapt pi to your workflows, not the other way around. [Read more →](PHILOSOPHY.md) > 🤖 **Vibe Coded** — This is a vibecoded project. It's here to inspire, not to be a polished product. Fork it, tear it apart, or use it as a starting point to build your own AI coding agent. ## 🚀 Quick Start ```bash # Clone and build git clone https://github.com/qhkm/pi-rs cd pi-rs cargo build --release # Run interactive mode ./target/release/pi # Or with a specific model pi --model claude-3-opus # Run a one-off task pi "Refactor src/main.rs to use async/await" ``` ## ✨ Features ### 🧩 Philosophy: Primitives, Not Features | What Others Bake In | How Pi Does It | |---------------------|----------------| | Sub-agents | Spawn via tmux, or build with extensions | | Plan mode | Write to files, or build with extensions | | Permission popups | Run in container, or build your own flow | | Built-in to-dos | Use TODO.md, or build with extensions | | MCP integration | Build as skills, or add via extensions | **The result:** A 15MB binary that starts in <50ms instead of 100MB+ and 1-3s. ### 🤖 AI Providers (17+ Supported) - **Anthropic**: Claude 3 Opus, Sonnet, Haiku - **OpenAI**: GPT-4o, GPT-4.1, o1, o3, o4-mini - **Google**: Gemini 2.5 Pro, 2.0 Flash - **Azure**: OpenAI GPT-4o, GPT-4.1 - **AWS**: Bedrock (Claude, Llama 4) - **Google Vertex**: Gemini 2.5, Claude - **Native**: Mistral, Groq, xAI (Grok), Cerebras, OpenRouter, MiniMax, HuggingFace, Perplexity, DeepSeek ### 🖥️ Terminal UI - **Streaming responses** with animated cursor - **Syntax highlighting** for code blocks - **Diff viewer** (unified & side-by-side) - **Model selector** (Ctrl+L) - **Thinking level selector** (Shift+Tab) - **Tool execution visualization** - **Fuzzy file search** (@file expansion) - **Theme system** with hot-reload ### 🛠️ Developer Tools - **7 built-in tools**: Read, Write, Edit, Bash, Grep, Find, Ls - **Smart truncation** with context preservation - **Diff editing** with conflict resolution - **Concurrent tool execution** - **Path security** (prevents directory traversal) ### 🔌 Extension System - **Shell extensions**: Bash scripts as tools - **Binary extensions**: JSON-RPC over stdio - **WASM extensions**: Sandboxed WebAssembly plugins - **Hook system**: Before/after turn events - **Command registration**: Custom slash commands ### 📝 Skills System - **Markdown-based**: Simple SKILL.md format - **YAML frontmatter**: Full metadata support - **Git install**: `pi /skill:install https://github.com/user/skill` - **Tag-based discovery**: Search by categories - **Auto-converted to tools**: Skills become available as agent tools ### 🔐 Authentication - **OAuth 2.0 Device Flow**: GitHub Copilot, Google Gemini, OpenAI Codex - **Encrypted storage**: XOR + keyring for tokens - **Auto-refresh**: Tokens refreshed before expiration - **API key fallback**: Environment variable support ## 📦 Installation ### From Source ```bash cargo install --path crates/pi-coding-agent ``` ### Homebrew (macOS/Linux) ```bash brew tap qhkm/pi brew install pi ``` ## 🎯 Usage ### Interactive Mode ```bash pi # Start interactive session pi --model gpt-4o # Use specific model pi --thinking high # Set reasoning level ``` ### One-shot Mode ```bash pi "explain this codebase" pi --file src/main.rs "refactor this" ``` ### JSON Mode ```bash pi --json "list all TODOs" | jq . ``` ### RPC Mode ```bash pi --rpc-server # Start JSON-RPC server ``` ### Slash Commands | Command | Description | |---------|-------------| | `/clear` | Clear conversation history | | `/compact` | Compact context to save tokens | | `/model <name>` | Switch AI model | | `/thinking <level>` | Set thinking level | | `/settings` | Open settings | | `/export` | Export conversation | | `/setkey <api-key>` | Set runtime API key for current session | | `/help` | Show help | ## ⚙️ Configuration ### Settings Hierarchy ``` ~/.pi/settings.json # User settings ./.pi/settings.json # Project settings (overrides user) ``` ### Example `.pi/settings.json` ```json { "model": "claude-3-opus", "thinking_level": "medium", "auto_compact": true, "max_turns": 50, "theme": "dark" } ``` ### AGENTS.md Place an `AGENTS.md` in your project root for project-specific instructions: ```markdown # Project Guidelines ## Code Style - Use snake_case for functions - Use PascalCase for types - Always handle errors explicitly ``` ## 🧩 Creating Extensions ### Extension Manifest (`extension.json`) ```json { "name": "my-extension", "version": "1.0.0", "description": "My custom tools", "tools": [ { "name": "lint", "description": "Run linter", "executor": "shell", "command": "cargo clippy -- -D warnings" } ] } ``` ### Installing Extensions ```bash # Place in .pi/extensions/my-extension/extension.json pi /extension:enable my-extension ``` ## 📝 Creating Skills ### Skill File (`SKILL.md`) ```markdown --- name: rust-best-practices description: Rust coding standards version: 1.0.0 author: Your Name tags: - rust - style --- # Rust Best Practices - Use `?` operator for error propagation - Prefer `&str` over `String` for parameters - Document all public APIs ``` ### Installing Skills ```bash pi /skill:install ./path/to/skill pi /skill:install https://github.com/user/skill-repo ``` ## 🎨 Theming Built-in themes: `dark`, `light`, `high-contrast` Custom theme (`~/.pi/theme.json`): ```json { "name": "custom", "fg": { "accent": "cyan", "success": "green" }, "syntax": { "keyword": "magenta", "string": "green" } } ``` ## 🏗️ Architecture ``` ┌─────────────────┐ │ pi (binary) │ ├─────────────────┤ │ pi-coding-agent│ ← CLI, modes, interactive ├─────────────────┤ │ pi-agent-core │ ← Agent loop, tools, hooks ├─────────────────┤ │ pi-ai │ ← LLM providers, streaming ├─────────────────┤ │ pi-tui │ ← Terminal UI components └─────────────────┘ ``` ### Workspace Crates | Crate | Purpose | Tests | |-------|---------|-------| | `pi-ai` | LLM providers, OAuth, models | 81 | | `pi-agent-core` | Agent loop, tools, context | 157 | | `pi-tui` | Terminal UI framework | 51 | | `pi-coding-agent` | CLI, modes, extensions | 28 | ## 🧪 Testing ```bash # Run all tests cargo test --workspace # Run specific crate tests cargo test -p pi-ai cargo test -p pi-agent-core cargo test -p pi-tui ``` ## 📊 Comparison | Metric | pi (Rust) | Others (Node/TS) | |--------|-----------|------------------| | Lines of Code | ~45K | ~128K+ | | Binary Size | ~15MB | 50-100MB+ (bundled) | | Startup Time | <50ms | 1-3s | | Memory Usage | ~50MB | 200MB+ | | Test Coverage | 461+ tests | Varies | ## 🤝 Contributing Contributions welcome! Please read our [Contributing Guide](CONTRIBUTING.md). ### Development ```bash # Run with logging RUST_LOG=debug cargo run --bin pi # Check formatting cargo fmt --check # Run clippy cargo clippy --workspace ``` ## 📄 License This project is licensed under the [MIT License](LICENSE). ## 🙏 Acknowledgments - Based on [pi-mono](https://github.com/badlogic/pi-mono) by [Mario Zechner](https://github.com/badlogic) — thank you for the original inspiration - Inspired by Claude Code and similar AI coding assistants - Built with [Tokio](https://tokio.rs), [Ratatui](https://github.com/ratatui-org/ratatui) concepts, and the Rust ecosystem - Thanks to all contributors ## 🔗 Related Projects - **[ZeptoClaw](https://github.com/qhkm/zeptoclaw)** — Ultra-lightweight (~4MB) personal AI assistant with multi-channel gateway (Telegram, Slack, Discord), container isolation, and agent swarms. A good complement if you need a server-deployable AI gateway rather than a terminal coding agent. --- <div align="center"> **[Philosophy](PHILOSOPHY.md)** • **[Documentation](https://docs.rs/pi-coding-agent)** • **[Issues](https://github.com/qhkm/pi-rs/issues)** • **[Discussions](https://github.com/qhkm/pi-rs/discussions)** </div>