qm

Multiplayer agent harness for work

9,227
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966
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TypeScript
语言
2026/8/23
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⚠️ 第三方软件声明

本 Skill 为第三方开源软件,独立托管于 GitHub。SkillTip 仅为信息目录,不控制或维护底层仓库。所显示的安全检查为自动化且范围有限,安装前请自行审查源码。

阅读服务条款

安装

添加到你的 Claude Code skills 目录:

# Add to your Claude Code skills
git clone https://github.com/yc-software/qm

快速入门

使用 qm 等 Skills 的指南。

安全报告

已验证

上次扫描:—

{
  "status": "PASSED",
  "issues": []
}

README.md

qm

A multiplayer agent harness for work. In Slack and on the web.

The QM web UI: two concurrent sessions, a sidebar of personal files, crons, keychain, deploys, memory, and skills

Setup

Tell your coding agent of choice Let's deploy https://github.com/yc-software/qm. From here, it should follow the deployment guide in this repo.

What is QM?

Most agents are designed like personal assistants. You can make one work for a whole company, but it quickly gets complex. QM is designed for startups. Employees each get their own isolated workspace and work independently without affecting each other, and they can also collaborate with the agent in channels, group messages, and projects.

Each person and each room has its own scoped memory, files, keychain view, permissions, crons, web apps, and durable sandbox.

It's built with open source in mind. Pick your own harness and model and switch between them — Pi, OpenCode, Codex, and Claude Code all drive the same core, so a deployment isn't tied to any single vendor.

Features

  • Personal and shared scopes. People customize the agent to be theirs, and still work with it collaboratively in Slack channels and projects.
  • Slack and web. The same identity and configuration carries between Slack and the web app.
  • Admin control. Set org-level configuration, a security posture, and which harnesses and models are available.
  • Web apps. Spin up custom internal apps and publish them to the right people.
  • Shared skills. Skills are scope-owned and shareable by grant, with admin-gated promotion to the whole org and skill packs imported from git repositories.
  • Background work. Crons, watches, and inbound webhooks run work while nobody's watching.

What you can do with it

  • Search internal notes, email, documents, databases, and the web together
  • Retrieve information from your company brain
  • Build internal apps, publish them to the right people, and keep their data current
  • Learn your writing voice from past sends, then triage your inbox on a schedule — labels and reply drafts included
  • Work in an existing repository: run tests, open PRs, monitor CI, check system logs
  • Track a project in a shared channel and post updates and follow-ups

Architecture

flowchart LR
  DB[("Postgres<br/>sessions · memory · queue")]

  subgraph CORE["Headless core"]
    API["API · identity · policy · scheduler"]
    LOOP["Agent loop<br/>(Pi, OpenCode, Claude Code)"]
    API <--> LOOP
  end

  SBX["Per-scope sandbox<br/>files · tools · logged-in services"]

  DB <--> API
  LOOP <--> SBX

Every turn runs through a central core, which can use a variety of models and harnesses to generate the response. A Postgres persistence layer holds user data, session history, and other durable state. The agent has a small, fixed tool surface; one of those tools is execute, which runs commands in the scope's own isolated sandbox — its durable computer, where installed tools stay installed. The web UI, the admin panel, and the public portal are optional plugins over the core's HTTP API; Slack is an optional in-process plugin that core starts and supervises through a direct service client.

The core runs TypeScript directly on Node and uses Fastify for HTTP. The Slack plugin uses Bolt; the web UI builds with Vite and renders with Lit.

The core itself is generic. Everything specific to one company — org config, custom tools and skills, sandbox image, infrastructure — lives in a deployment directory that the qm CLI validates and deploys. Every substrate (harness, session store, sandbox, memory) sits behind an interface, so production implementations swap in via one wiring file.

Security and secrets

QM's approach follows local coding agents like OpenCode, Codex, and Claude Code: the agent acts as the person it's working for, with their credentials and permissions, and everything it does is audited. An org picks one security posture, which narrower scopes can only tighten:

  • Strict — every harness tool call pauses for human approval, except the two no-effect turn enders.
  • Auto (default) — a classifier screens provenance-labelled external data and tool results before they reach the model; a deployment can point that at its own screening proxy.
  • Dangerous — no content screening, no pauses between tool calls.

The predeclared command policy — approval rules and hard denials for things like recursive deletes or destructive SQL — applies in every posture, Dangerous included.

SECURITY.md has the threat model, the operator assumptions, and the known limitations.

Deploy it for your org

Create an organization-owned deployment repository that depends on @yc-software/qm:

npm exec --yes --package=@yc-software/qm@latest -- \
  qm init . --org <slug> --target <fly-or-aws>
npm install

Initialization materializes a deployment skill for an agent and walks through infrastructure, web sign-in, connector credentials, optional Slack access, deployment, and live verification — no source checkout required. Each deployment runs in the operator's own cloud account; initialization does not generate or enable deployment CI, and this repository has no production deployment workflow. See deployment.md for the details.

Contributing

We take contributions as human-written text, not code — see CONTRIBUTING.md. Describe the change you'd like informally in a .txt or .md file in adrs/, and if we're aligned we'll handle the implementation. Report vulnerabilities privately — see SECURITY.md, not a public issue.

Customize your instance

The deployment repository above carries config and a sandbox layer, and never needs a source checkout. Some organizations want the opposite trade: the whole codebase in one place, so engineers and coding agents read core and customizations together, while the customizations themselves stay private. For that, keep a private fork: a standalone private repository whose history begins as a clone of qm and whose core stays identical to upstream.

Populate it once, then clone it to work in:

gh repo create <org>/qm-private --private

git clone --bare git@github.com:yc-software/qm qm-seed.git
git -C qm-seed.git push --mirror git@github.com:<org>/qm-private
rm -rf qm-seed.git

git clone git@github.com:<org>/qm-private
git -C qm-private remote add upstream git@github.com:yc-software/qm

Create the private fork with a plain clone, as shown above, and never with GitHub's fork feature. The word "fork" here names the concept — a downstream copy that diverges deliberately and merges from upstream — not GitHub's Fork button. A GitHub fork inherits the visibility of the repository it came from, so a fork of a public repository cannot be made private. A GitHub fork also shares one object network with the repository it came from, so commits pushed to the fork stay fetchable by SHA from the public side. Many organizations disallow forking private repositories as well. A plain clone has none of these problems, and it costs one thing: the clone is an ordinary repository, so upstream's CI workflows run live in your own account. Expect to supply the secrets those workflows need, or disable the ones you do not want running.

Everything specific to your organization goes in deploy/layers/<org>/ — config, sandbox tools and skills, plugin images, infrastructure — in the same shape qm init produces. See deploy/layers/README.md. Core stays byte-identical to upstream, which is what keeps merges small.

Two skills maintain the boundary in both directions. update-qm merges upstream qm into the private fork and opens the sync PR; upstream-pr sends an organization-agnostic fix back to qm, cutting the branch from upstream/main and checking the outgoing diff, commit messages, and screenshots for organization identifiers before it pushes. Nothing under deploy/layers/ ever travels upstream.

Going deeper

License

Except where otherwise noted, QM is available under the MIT License.

常见问题

What is qm?

qm is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by yc-software. Multiplayer agent harness for work. It has 9,227 GitHub stars.

Is qm safe to use?

qm returned warnings in SkillsLLM's automated security scan. It has no critical vulnerabilities, but review the flagged issues in the Security Report section before adding it to your workflow.

How do I install qm?

Clone the repository with "git clone https://github.com/yc-software/qm" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is qm written in?

qm is primarily written in TypeScript. It is open-source under yc-software on GitHub, so you can review or fork the full source.

Are there alternatives to qm?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh qm against similar tools.

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