Octomind 开源 Rust 编码智能体框架发布
Octomind – open-source AI harness that saves your tokens, static rust
Octomind 发布开源编码智能体框架,单个 Rust 二进制支持交互式、stdin、守护进程、WebSocket 和 ACP 五种运行方式,通过 MCP 工具读写文件、执行 shell 和调用子智能体。
Open-source coding agent harness. One Rust binary, any model, every surface.
Interactive, stdin, daemon, WebSocket, or ACP — one engine, one config.
A supervising model plans and checks the work.
Policy lives in TOML guardrails, not approval prompts.
Website · Docs · Tap Registry · Benchmarks · Issues
Octomind is an open-source coding agent harness. It gives an LLM real access to your repo — reading and writing files, running shells, searching code, delegating to sub-agents — through MCP tools. The same harness runs interactively, non-interactively through stdin, as a background daemon, over WebSocket, or as an ACP agent inside your editor or another agent's stack.
# Interactive octomind run developer:general # Piped — CI, scripts, automation echo "Explain the auth module" | octomind run developer:general --format plain # Daemon — keep it alive, talk to it from another terminal echo "watch the build" | octomind run --name watcher --daemon --format jsonl octomind send --name watcher "run the test suite"
Why Octomind?
Most coding agents assume a human is watching the screen. Octomind is built for the work that keeps going after you leave.
- Policy as code, not approval popups. Deterministic guardrails — pre-call guards, post-result hooks, post-turn validators — live in TOML and scripts, so they work in CI, daemons, and scheduled runs.
- Proven on real PRs. It solved 24 of 25 held-out tasks at lower cost than the closest competitor. See the benchmarks.
- Ready-made specialists.
octomind run developer:generalpulls a packaged agent (prompt, model, MCP servers, tool permissions) from a tap. Publish your own with one repo. - Sessions that stay sharp. Adaptive compression keeps long tasks moving while retaining task knowledge and the live exchange.
- Remembers your rules. Rules and corrections you state in a session become lessons, grounded in your own words and scoped to the project and role, that come back in later sessions. See learning.
- Any model, any budget. Use Octomind Cloud or your own key (OpenRouter, Anthropic, OpenAI, DeepSeek, Ollama, and more), pick a model per role, and cap spend per request and per session. Over budget, a terminal session asks y/N; a non-interactive run stops with exit code 75.
- One config. Models, tools, roles, guardrails, budgets: all TOML, no framework code.
Quick Start
1. Install (macOS, Linux):
curl -fsSL https://raw.githubusercontent.com/muvon/octomind/master/install.sh | bashOn Windows, in PowerShell:
irm https://raw.githubusercontent.com/muvon/octomind/master/install.ps1 | iex
On macOS, you can also install with Homebrew:
brew install muvon/tap/octomind
2. Get model access. The fastest path is Octomind Cloud, which includes models and needs no configuration:
octomind login
Prefer your own provider key? Skip login and export one (also OPENAI_API_KEY, ANTHROPIC_API_KEY, DEEPSEEK_API_KEY), then follow Model access to point the config at it:
export OPENROUTER_API_KEY="your_key"
3. Run a specialist in your project:
cd ~/your/project octomind run developer:general
You're now in a session with an agent that can read your code, run commands, and edit files. The interface is a plain line prompt with markdown rendering — no TUI to learn, so it works over SSH, in tmux, and in CI logs. The first time you run a specialist, it may install its tools and ask for credentials.
developer:generalcomes from the default tapmuvon/tap, not your local config. Plainoctomind runstarts the config's default role,assistant:concierge.
Try the recorded bug-fix demo: two failing tests, an agent fix, and an independent test rerun.
Benchmarks
Measured on octobench against 25 tasks harvested from merged pull requests across Python, PHP, Rust, C++, and JavaScript. Each agent works in the pre-fix repo; held-out tests from the merged fix decide pass or fail. These are the published July 30, 2026 results, not a measurement of this checkout.
| solved | judge Σ / 2500 | cost | wall time | |
|---|---|---|---|---|
| octomind + glm-5.2 | 24/25 | 2264 | $63.43 | 3.6h |
| claude code + claude-opus-5 | 23/25 | 2262 | $81.79 | 6.7h |
| codex + gpt-5.6-sol | 21/25 | 2127 | $14.86 | 1.0h |
| opencode + glm-5.2 | 19/25 | 2093 | $129.54 | 3.3h |
- The harness matters. opencode used the same model and endpoint; octomind solved 24 vs 19 at roughly half the cost. All four agents ran stock invocations with no tuning, so this measures the whole harness, not individual features.
- Worst-case pricing, still ahead. glm-5.2 ran without prompt caching while Opus billed ~97% of context re-reads at cache rates — and octomind still led on solves, cost, and wall time.
- Reproducible. Per-case table, artifacts, and reproduction guide: BENCHMARK.md. Background: blog post.
Guardrails: Policy as Code
Drop a .agents/guardrails.toml in your repo. Octomind enforces it deterministically, with no code to compile and no plugin to install.
# Pre-call deny — block a class of calls before they execute [[guard]] match = "shell(command=^rm\\s+-rf?)" message = "rm -rf blocked." # Conditional rule — only fires after the agent ran git status this session [[guard]] match = "shell(command=git push)" when = ["+shell(command=git status)"] message = "Review changes before pushing."
| Layer | When it runs | What it does |
|---|---|---|
| Guards | Before a tool call | Deny by capability, argument regex, and session history. A match returns a denial instead of executing the call. |
| Hooks | After a tool result | A non-zero exit injects stdout into the agent's inbox — lint and format failures become automatic corrections without restarting the turn. |
| Validators | After a turn | Scripts the agent reads on its next turn. This replaces "approve this change?" prompts in autonomous loops. |
If you know Claude Code hooks: guards are PreToolUse denies declared in TOML, hooks are PostToolUse, validators are Stop — no scripts required for the common cases.
Hook and validator script examples: Guardrails guide.
One Harness, Five Surfaces
The same harness, exposed wherever your workflow needs it.
| Surface | Use it for | Docs |
|---|---|---|
| Interactive CLI | Daily work, any domain | Sessions |
Non-interactive (--format plain / jsonl) |
CI, scripts, scheduled jobs | CLI reference |
Daemon + send |
Background agents, continuous monitoring | Daemon & hooks |
WebSocket (octomind server) |
IDE plugins, dashboards, integrations | WebSocket server |
ACP (octomind acp) |
Agent inside Zed, JetBrains, VS Code, Neovim, or any ACP editor | ACP protocol |
Need machine-readable results? Pass --schema schema.json to constrain the final response to a JSON Schema (requires a model with structured-output support). See Structured output.
Features
| Feature | What you get | Learn more |
|---|---|---|
| Specialists & taps | Packaged agents with model, prompt, MCP servers, and permissions; installs their tool dependencies on first use | Tap system |
| Roles | Per-role model, temperature, system prompt, tools | Roles |
| Workflows | Multi-step pipelines, each step with its own model and toolset | Workflows |
| MCP client | stdio and Streamable HTTP servers, with OAuth; enable/disable servers mid-session | MCP tools |
| Agent Skills | Standard SKILL.md skills from .agents/skills/, ~/.config/agents/skills/, and taps; they activate on demand, so your context stays small |
Skills |
| Local project tools | Executable scripts in .agents/tools/ auto-register as tools |
Local tools |
Plugins & AGENTS.md |
Agent Plugins (plugin.json + skills + mcp.json) from taps, .agents/plugins/, or ~/.config/agents/plugins/; project AGENTS.md loads at session start |
Configuration |
| Supervisor & learning | A second model plans, gates completion, and condenses tool output; lessons persist as files per project and role | Supervisor, Learning |
| Sandbox | --sandbox locks writes to the working directory via Landlock (Linux) or Seatbelt (macOS), inherited by every shell, MCP server, and sub-agent |
Config reference |
| Token efficiency | Cache-aware cost accounting and adaptive compression | Token efficiency |
Specialists
octomind run developer:general # general dev, language skills auto-activate octomind run doctor:blood # blood-test interpretation specialist octomind run lawyer:sg # legal specialist
Running a specialist fetches its manifest from the tap registry, installs any required binaries, resolves credentials, starts the right MCP servers, and then opens the session.
Build and register your own:
octomind tap init yourteam/my-tap # scaffold, validate, git-init, and register locally octomind tap yourteam/my-tap # on another machine, after publishing to GitHub
The octomind- prefix is added automatically: yourteam/my-tap maps to the repository
yourteam/octomind-my-tap.
Installation
| Method | Command |
|---|---|
| Install script (recommended) | curl -fsSL https://raw.githubusercontent.com/muvon/octomind/master/install.sh | bash |
| Install script (Windows PowerShell) | irm https://raw.githubusercontent.com/muvon/octomind/master/install.ps1 | iex |
| Homebrew (macOS) | brew install muvon/tap/octomind |
| Scoop (Windows) | scoop bucket add muvon https://github.com/Muvon/scoop-bucket then scoop install muvon/octomind |
| Cargo (Rust 1.95+) | cargo install octomind |
| Docker | docker run --rm ghcr.io/muvon/octomind --help |
| From source | git clone https://github.com/muvon/octomind.git && cd octomind && cargo build --release |
The install script detects your OS and architecture (Linux and macOS on x86_64/aarch64) and installs to ~/.local/bin/. Pass --install-dir <DIR> or set OCTOMIND_INSTALL_DIR to override. On Windows (x86_64/aarch64), install.ps1 installs to %LOCALAPPDATA%\octomind\bin and adds it to your user PATH; it honors OCTOMIND_INSTALL_DIR and OCTOMIND_VERSION too. install.sh still works from Git Bash or MSYS2.
Command not found? Add the install directory to your PATH:
export PATH="$HOME/.local/bin:$PATH"
Building from source requires protoc; see Building from source for per-OS prerequisites.
Verify:
octomind --version octomind config # generate the default config octomind run # start your first session
Shell completions: octomind completion <bash|zsh|fish|elvish|powershell>.
Model access
Octomind Cloud — octomind login (device-code sign-in, like gh auth login) stores a gateway key locally. The default config already uses octohub:auto. Learn more.
Bring your own key — set the provider's environment variable (OPENROUTER_API_KEY, OPENAI_API_KEY, ANTHROPIC_API_KEY, DEEPSEEK_API_KEY, …) and point the model tables at it. The supervisor and compression profiles also default to octohub:auto, so update all three:
[model] name = "anthropic:claude-sonnet-5-5" [supervisor.model] name = "anthropic:claude-haiku-5-5" [compression.model] name = "anthropic:claude-haiku-5-5"
Provider details and per-role overrides: Providers & models.
Configuration
Config lives at ~/.local/share/octomind/config/config.toml on macOS and Linux, and under %LOCALAPPDATA%/octomind/config/ on Windows. Set OCTOMIND_DATA_DIR to override the data root.
octomind config --show # view current config octomind config --validate # validate config
Override any value for a single run with -c:
octomind run -c supervisor.enabled=false
Full reference: Configuration reference · Environment variables.
Session commands
| Command | Description |
|---|---|
/help |
Show all commands |
/info |
Token usage and costs |
/model anthropic:claude-sonnet-5-5 |
Switch model mid-session |
/role developer:general |
Switch to a configured role or tap tag |
/new Review auth |
Start a fresh session (title optional) |
/done |
Force context compression and start background learning extraction when enabled |
/exit |
Exit the session |
Full list: Session commands.
Telemetry
Octomind reports anonymous usage: which commands, tools, and models are used, plus timings, token counts, and error kinds. It never sends your code, prompts, file paths, tool arguments, or environment values. Opt out in any of three ways:
export DO_NOT_TRACK=1 # the cross-tool standard, honored first export OCTOMIND_TELEMETRY=0 # for subsequent commands in this shell # or set `telemetry = false` in config.toml
Exact field list: Telemetry.
Documentation
| Start here | Go deeper | Integrate | Reference |
|---|---|---|---|
| Installation | Roles | WebSocket server | CLI |
| Quickstart | Workflows | ACP protocol | Config |
| Configuration | Compression | Daemon & hooks | Session commands |
| Providers & models | Guardrails | Editor integration | Environment variables |
Full index: doc/README.md · Hosted: octomind.run/docs.
Contributing
The most impactful contribution isn't code — it's specialist agents. A cardiologist publishing doctor:medications. A tax attorney publishing lawyer:us. A security researcher publishing security:owasp. One TOML file, and everyone facing that problem gets a specialist-grade AI.
Code contributions are welcome too. Set up the hooks and run the gate before you push:
pip install pre-commit && pre-commit install make dev # fmt + clippy + test
Commits follow Conventional Commits. Full guide, architecture overview, and code conventions: CONTRIBUTING.md · internals: Architecture.
Community participation follows our Code of Conduct. Report vulnerabilities privately using the security policy.
License
Apache License 2.0 — see LICENSE.
来源:Hacker News · github.com
