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genai-io/san

< SAN ✦ />

A fast, open agent harness for the terminal

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~0.01s cold start  ·  📦 ~12 MB single binary  ·  🪶 zero runtime deps

San is an open-source agent harness for the terminal — one native Go binary that wraps any model in a fast, inspectable, permission-gated loop. Bring your own model and extensions; there's no Node.js or Python runtime to install.

Why San

  • Fast — a ~12 MB single binary, ~0.01s cold start, no separate runtime.
  • Open — swap the model, search, and tools at runtime; bring your own persona profiles and extensions.
  • Harness — tune policies, not just parts: customize autopilot to cut human-in-the-loop, and self-learning — memory and skills it grows and refines — as you work.

The name — San, written ("three") and drawn . From the Dao De Jing, 三生万物 — "three begets the ten-thousand things": one runtime that becomes any agent, running a three-step loop (reason → act → observe). The command stays san.

Features

Open architecture  ·  overview diagram
San — pluggable models, search backends, personas, skills & extensions, and a self-evolving agent
  • Models — Anthropic, OpenAI, Google, DeepSeek, Moonshot, Alibaba, MiniMax, Z.ai (GLM), SenseNova, Mimo, Volcengine (Ark), Ollama (local), Agnes-AI. /model
  • Search — Exa, Tavily, Brave, Serper. /search
  • Personas & extensions — reusable profiles, plus Claude Code skills, plugins, MCP servers, hooks, and sandboxed subagents — all run unmodified. /persona
  • Self-learning — opt-in; distills durable memory and reusable skills with configurable cadence and caps. (Level 1; deeper levels on the way.)

Engineering

  • Runs anywhere — one static binary for Windows, macOS, and Linux; the same file runs on a laptop, an edge device, or a scratch container (footprint · benchmark).
  • Permissions — three modes (ask · auto-accept · autopilot) toggled with Shift+Tab; subagents inherit the gates (details).
  • Sessions — auto-save, resume (--continue / --resume), fork (/fork), auto-compaction (/compact), and per-message cost tracking.
  • Inspector — replay transcripts and inspect system prompts in a local web UI (san inspector).
  • Plus event-driven subagent coordination, TUI themes, and prompt prediction.

Installation

macOS / Linux

curl -fsSL https://raw.githubusercontent.com/genai-io/san/main/install.sh | bash

Windows (PowerShell)

irm https://raw.githubusercontent.com/genai-io/san/main/install.ps1 | iex

Re-run to upgrade.

Other methods

Uninstall

# macOS / Linux
curl -fsSL https://raw.githubusercontent.com/genai-io/san/main/install.sh | bash -s uninstall
# Windows (PowerShell)
& ([scriptblock]::Create((irm https://raw.githubusercontent.com/genai-io/san/main/install.ps1))) uninstall

Go Install

go install github.com/genai-io/san/cmd/san@latest

Build from Source

git clone https://github.com/genai-io/san.git
cd san
go build -o san ./cmd/san
mkdir -p ~/.local/bin && mv san ~/.local/bin/

Usage

san                              # interactive
san "explain this function"      # one-shot
san -p "do something"            # print mode (no TUI), pipe-friendly
san --continue                   # resume the latest session
san --resume                     # pick a past session to resume

# Subcommands (run `san <command> --help` for the full list)
san inspector                    # session transcript viewer
san agent run --type Explore --prompt "..."   # run a headless agent
san plugin <list|install|enable|...>          # manage plugins
san mcp <add|list|remove|...>                 # manage MCP servers
What How
Pick / switch model /model — saved to ~/.san/providers.json
Cycle thinking budget Ctrl+T or /think (levels vary by provider)
Toggle permission mode Shift+Tab (ask · auto-accept · autopilot)
Search / persona / memory /search · /persona · /memory
Skills / agents / tools /skills · /agents · /tools
Plugins / MCP / config /plugin · /mcp · /config
Session / loop / misc /fork · /compact · /loop · /glob · /init · /clear
All slash commands /help
Send · newline · stop Enter · Alt+Enter · Esc
Expand tool · cancel · exit Ctrl+O · Ctrl+C · Ctrl+D

For API keys, set the matching env var (see Credentials below) or paste when prompted on first launch. Full walkthrough: docs/guides/getting-started.md.

Configuration

Config lives in ~/.san/ (user) and <project>/.san/ (project, overrides user). A SAN.md or CLAUDE.md at the project root is auto-loaded into the system prompt.

Credentials
Service Variable
Anthropic (Claude) ANTHROPIC_API_KEY or Vertex AI
OpenAI (GPT, o-series, Codex) OPENAI_API_KEY, or a ChatGPT subscription (sign in via /model)
Google (Gemini) GOOGLE_API_KEY
DeepSeek (DeepSeek V4) DEEPSEEK_API_KEY
Moonshot (Kimi) MOONSHOT_API_KEY
Alibaba (Qwen) DASHSCOPE_API_KEY
MiniMax MINIMAX_API_KEY
Z.ai (GLM / GLM Coding Plan) BIGMODEL_API_KEY
SenseNova SENSENOVA_API_KEY
Mimo MIMO_API_KEY
Volcengine (Ark) VOLCENGINE_API_KEY
Ollama (local) OLLAMA_BASE_URL (default http://localhost:11434/v1)
Agnes-AI AGNESAI_API_KEY
Exa search none (default)
Tavily search TAVILY_API_KEY
Brave search BRAVE_API_KEY
Serper search SERPER_API_KEY
Directory layout

User-level (~/.san/):

providers.json    # Provider connections and current model
settings.json     # Permissions, hooks, env, active persona
skills.json       # Skill states
personas/         # Persona bundles: system prompt parts, skills, settings
skills/           # Custom skill definitions
agents/           # Custom agent definitions
commands/         # Custom slash commands
plugins/          # Installed plugins
projects/         # Session transcripts + indexes

Project-level (.san/):

settings.json       # Permissions, hooks, disabled tools
mcp.json            # MCP server definitions (team shared)
mcp.local.json      # MCP server definitions (personal, git-ignored)
personas/           # Project-scoped persona bundles (override user-level)
agents/*.md         # Subagent definitions
skills/*/SKILL.md   # Skills
commands/*.md       # Slash commands
plugins/            # Project-level plugins
plugins-local/      # Local plugins (git-ignored)

Benchmark: San vs Claude Code

Compared with Claude Code v2.1.112 on Apple Silicon, same model (claude-sonnet-4-6):

Metric San Claude Code Advantage
Download size 12 MB 63 MB (+ Node.js 112 MB) 5x smaller
Disk footprint 38 MB 175 MB 4.6x smaller
Startup time ~0.01s ~0.20s 20x faster
Startup memory ~32 MB ~189 MB 5.8x less
Simple task ~2.4s / 39 MB ~10.4s / 286 MB 4.3x faster, 7.3x less memory
Tool-use task ~3.3s / 39 MB ~26.0s / 285 MB 7.9x faster, 7.2x less memory

Both tools have comparable features (hooks, skills, plugins, session, MCP, etc.). The performance gap comes from Go's native compilation, minimal architecture design, and lean prompt engineering — vs Node.js V8/JIT/GC runtime overhead.

See full details: docs/operations/benchmark.md

Documentation

Related Projects

  • Claude Code — Anthropic's AI coding assistant
  • Aider — AI pair programming in terminal
  • Continue — Open-source AI code assistant

Community

Two ways in — WeChat for the Chinese community, Slack for everyone else:

WeChat official account 极客外传 QR code
关注公众号「极客外传」· 回复 san 入群
San Slack QR code
Scan or join our Slack

Contributing

Contributions welcome! See CONTRIBUTING.md for guidelines.

License

Apache License 2.0 - see LICENSE for details.

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Fast, open agent harness for the terminal. One ~12 MB Go binary — bring any model and extensions into a single inspectable loop that learns as you work.

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