metis

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SUMMARY

Metis is a coding agent that boosts coding performance by 50%

README.md

Metis pixel mark

English · 简体中文

TypeScript npm version Node.js 22.19.0 or newer MIT License

A coding agent that searches, remembers, executes, and verifies across terminal and desktop.

Quick start · Highlights · How it works · Documentation


Metis Desktop workspace

Quick start

Desktop installation

Desktop includes the Metis CLI and Server runtime; Node.js is not required separately.

Platform Build Install
macOS Apple silicon (arm64) Download Metis-*-macos-arm64.dmg, then drag Metis.app to Applications.
Windows x64 Run Metis-*-win-x64-setup.exe, or extract Metis-*-win-x64.zip and launch Metis.exe.

Download files and matching .sha256 checksums from the latest GitHub Release. If Windows SmartScreen reports an unknown publisher, continue only when the file came from the official release page and its checksum matches.

CLI installation

Requires Node.js >=22.19.0 and npm.

npm install -g --ignore-scripts @wholiver_hu/metis@latest
metis

Use /login for supported subscription providers, or configure an API key. Run metis --help for CLI options and see the Quickstart for the complete first-run flow.

Highlights

  • Plan and Build workflows — investigate safely in read-only Plan mode, then execute an approved proposal with a persistent checklist in Build mode.
  • Durable memory and recovery — search reusable project knowledge and resume work after interruption, compaction, or session reload.
  • Flexible models and authentication — use built-in subscription login, API-key providers, or custom OpenAI-compatible providers with model discovery.
  • Desktop workspace — attach images, videos, text, and other files through the picker, clipboard, or drag and drop; manage providers and sessions graphically.
  • Recursive Multi-Agent System — native named agent definitions (coordinator, planner, implementer, reviewer, verifier), L0→L4 recursive delegation, role-based tool sandboxing, physical Git Worktree isolation, and deterministic lifecycle control.
  • TerminalBench & Harbor Ready — headless machine-readable JSONL execution, standardized exit codes (0/1/2), final answer separation, full trace aggregation, and official Python harness adapters.
  • Video evidence — inspect local video through metadata, timestamped storyboards, ordered motion samples, high-resolution frames, subtitles, and local transcription.
  • Extensible core — add TypeScript extensions, Agent Skills, prompt templates, themes, and Metis packages; integrate through print, JSON, RPC, Server, or the Node.js SDK.
  • Verified execution — coordinate subagents, preserve tool-result ordering, run relevant checks, and compare delivery against the original request.

How Metis works

  1. Ground — load trusted instructions and relevant context, then search code, memory, or authoritative sources when needed.
  2. Plan or build — Plan mode stays read-only and produces a durable proposal; Build mode performs evidence-supported changes.
  3. Persist — retain sessions, message/tool pairs, workflow checkpoints, plans, and compacted context.
  4. Verify — run risk-proportionate checks and report completed requirements, evidence, and remaining risk.
Technical design

Deterministic workflow runtime

Metis freezes a StepSnapshot before every model sample. Model, reasoning level, collaboration mode, instructions, messages, visible tools, dispatcher, and context window therefore remain consistent for that step. Safe reads may run in parallel; writes and mixed tools are serialized. Steering and follow-ups are applied only after current tool results persist.

Plans and interactive input

New interactive and Desktop sessions start in Plan mode. /mode plan and /mode build switch workflows when idle. Approved proposals survive reload and compaction through read_plan; Build checklists update in place in TUI and Desktop. Interactive hosts can answer ask_user, while unattended print/JSON and SDK runs return a recoverable unsupported result instead of hanging.

Memory

Metis checkpoints active work after prompts, completed steps, compaction, errors, aborts, and completion. Durable records and their search index live in ~/.metis/memories/state.sqlite. query_memory_db is available on demand in Plan and Build; results are advisory and never override current instructions.

Use /memory status|on|off|run|search|forget|reset. Proposal artifacts and long-term memory remain separate, so an unexecuted draft is not promoted automatically.

Performance example

User test comparing Metis and OpenCode task completion time

In one user test on the same task, Metis finished in 1 minute 30 seconds and OpenCode in 3 minutes 30 seconds, with no observed accuracy difference. This single comparison is not a universal benchmark; results depend on the task, model, tools, and environment.

Documentation

Topic Guide
Install, authenticate, and start Quickstart
Commands and interactive usage Using Metis
Providers and custom models Providers · Custom models
Multi-Agent System Named Agents & Delegation
Benchmark & Evaluation TerminalBench & Harbor
Sessions and compaction Sessions · Compaction
Extensions, skills, and packages Extensions · Skills · Packages
Programmatic integration SDK · RPC · JSON
Video inspection Video tool
Security and configuration Security · Settings

See the documentation index for every guide.

Developer information
npm run build                 # Compile TypeScript and copy runtime assets
npm test                      # Run the Vitest suite
npm run clean                 # Remove compiled output
npm run build:binary          # Build the standalone binary

The package exports the Node.js SDK from @wholiver_hu/metis and the RPC entry point from @wholiver_hu/metis/rpc-entry.

Contributing

Contributions are welcome. See CONTRIBUTING.md for development, Extension and Package integration, testing, and AI-assisted contribution guidance.

License

Distributed under the MIT License.

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