Harmonist
Portable AI agent orchestration with mechanical protocol enforcement. 186 agents, zero runtime dependencies.
Install
git clone https://github.com/GammaLabTechnologies/harmonistInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →If you are an AI agent asked to install or integrate this pack: read
integration-prompt.mdand execute its steps. Do not applyAGENTS.template.mdas a live rule inside the pack folder — it is the template that becomes the user project'sAGENTS.mdduring integration.
Harmonist
Portable AI agent orchestration with mechanical protocol enforcement
A drop-in multi-agent framework for Cursor, Claude Code, Copilot, Windsurf, Aider, and other AI coding assistants.
Built and maintained by GammaLab · @GammaLabTechnologies
Most AI coding frameworks trust the language model to follow the rules. Harmonist refuses to let it skip them. Every code-changing turn is gated by hooks that check whether the required reviewers ran, whether memory was updated, and whether the supply chain of every shipped file is intact. If the checks fail, the turn doesn't complete — no matter how confidently the model claims it's done.
This is the first open-source agent framework where protocol enforcement is a mechanical gate, not a polite request in a prompt.
Table of contents
- Why Harmonist exists
- What makes it different
- Requirements
- Quick start
- Architecture
- The 193-agent catalogue
- Mechanical enforcement
- Structured validated memory
- Supply-chain integrity
- Supported IDE integrations
- Key scripts
- Documentation
- Testing
- FAQ
- Contributing
- Security
- License
- About GammaLab
Why Harmonist exists
AI coding assistants have a structural problem that prompt engineering alone cannot fix.
The problem: every serious engineering workflow has non-negotiable rules — "no floating-point for money", "run QA before merging", "every external call retries with idempotency keys", "security review before touching auth code". An LLM can be told to follow them, but there is no mechanism forcing it to. It can agree, move on, and silently skip the step. On a good day you notice. On a bad day the bug ships.
The current landscape is split between two imperfect answers:
- Thin agent frameworks (LangChain, CrewAI, AutoGen, MetaGPT and many others) give you orchestration primitives but leave enforcement to the prompt. The model can always override its own protocol.
- Heavy enterprise platforms promise governance through separate runtimes, databases, and vendor lock-in — but need infrastructure to install, don't work on a solo developer's laptop, and can't be audited file-by-file.
Harmonist takes a different stance. Protocol enforcement is
implemented as IDE-level hooks — concrete shell and Python scripts that
observe every subagent dispatch, every file edit, every session stop.
When the rules the project declared aren't met, the stop hook
returns a followup_message to the AI and refuses to allow the turn
to complete. The model can't argue with that; it's a state machine on
disk.
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