by yc-software
Multiplayer agent harness for work
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# Add to your Claude Code skills
git clone https://github.com/yc-software/qmGuides for using ai agents skills like qm.
A multiplayer agent harness for work. In Slack and on the web.

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.
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.
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:
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.
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.
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.
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.
docs/getting-started.md — first run, end to endcli/README.md — the qm CLI and the deployment directory contractdocs/deploy-directory.md — the deployment directory in full.env.example — every knob, documented in placeplugins/ — the surfaces (Slack, web UI, admin, portal)Except where otherwise noted, QM is available under the MIT License.
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.
qm's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
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).
qm is primarily written in TypeScript. It is open-source under yc-software on GitHub, so you can review or fork the full source.
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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