Octomind – open-source AI harness that saves your tokens, static rust

Source: github.com
41 points by donk8r 2 hours ago on hackernews | 32 comments

Octomind — open-source AI coding agent runtime

The CLI-first AI coding agent runtime.

Pipe it, schedule it, embed it. One binary, any model, MCP-native —
built for autonomous work, not just chat.

CI Crates.io Coverage License Stars

Website · Docs · Tap Registry · Benchmarks · Issues

Octomind mascot: a pixel-art purple octopus with cyan eyes and waving tentacles


Octomind is a CLI-first AI coding agent runtime. 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 session engine works interactively, piped through stdin, as a background daemon, over WebSocket, or as an ACP sub-agent inside 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:general pulls 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.
  • Any model, any budget. Use Octomind Cloud or your own key (OpenRouter, Anthropic, OpenAI, DeepSeek, Ollama, and more), pick a model per role, and set spend thresholds per request and per session. A request over its threshold stops; at the session threshold a terminal session asks y/N before continuing, while a non-interactive octomind 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 | bash

On 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:

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:general comes from the default tap muvon/tap, not your local config. Plain octomind run starts 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. The runtime 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.

Hook and validator script examples: Guardrails guide.

Five Ways to Run It

The same session engine, exposed however your workflow needs it.

Surface Use it for Docs
Interactive CLI Daily work, any domain Sessions
Piped (--format plain / jsonl) CI/CD, shell scripts, automation CLI reference
Daemon + send Background agents, continuous monitoring Daemon & hooks
WebSocket (octomind server) IDE plugins, dashboards, integrations WebSocket server
ACP (octomind acp) Sub-agent inside another agent or 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
Intent-driven context Skills and capabilities activate on demand, keeping context small Skills
Local project tools Executable scripts in .agents/tools/ auto-register as tools Local tools
Supervisor & learning External planning and gating; file-backed learning records Supervisor, Learning
Sandbox --sandbox restricts filesystem writes to the working directory Config reference
Token efficiency Cache-aware accounting and compaction 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 = "openrouter:google/gemini-2.5-flash"

[supervisor.model]
name = "openrouter:google/gemini-2.5-flash"

[compression.model]
name = "openrouter:google/gemini-2.5-flash"

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-haiku-4-5 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.