Hive is a co-maintainer for your GitHub project that never sleeps. Point it at a repo, set the limits, and let short-lived AI agents handle the maintenance chores while humans keep the decisions that matter.
Hive watches the work that piles up in a repository — issues, pull requests, failing CI, CVEs, and dependabot alerts — and sends AI coding agents (Claude, Copilot, Codex, Antigravity, Goose…) to deal with it: triage, fixes, reviews, releases. You decide how much it is allowed to do. Humans keep every decision that matters; agents do the chores.
A terminal agent is a power tool: you hold it, aim it, and it stops when you stop. Hive is the workshop that runs the power tools for you — on three rules the industry is only now discovering:
- Short-lived agents. Every task starts a fresh agent with a clean context and ends it. No "long-running" agent drifting for hours.
- External context. What the agent needs to know lives outside the model — in your repo, your knowledge base, your audit trail — and is re-injected each time, so nothing is forgotten and nothing is hallucinated from stale memory.
- Prompts driven by deterministic facts. The instructions an agent gets are templates filled from real data (the issue, the CI log, the diff, the trust level), not hand-tuned prose.
Around that, Hive picks work from your real queue, sets limits in code with six trust levels from the AI Codebase Maturity Model (ACMM) — a framework for how much autonomy a codebase is ready to give agents (levels · paper), checks before and after with deterministic filters and gates, writes every action to an audit log owned by a named human, and runs around the clock. Same agents you use today — governed, scheduled, scoped, and accountable.
- Spoke — one running Hive, serving your repo(s). It is where agents actually work. Runs on your Kubernetes cluster, Podman, or Docker Compose.
- Hub — the control plane for many spokes: registers, provisions, upgrades and watches them; fleet view, leaderboards, routes contributor compute to the hives that need it.
A spoke works alone. A hub is how you see and manage a fleet of them.
Your own agents are only the start. The contributor relay (ClankeR) lets anyone who wants to help your project donate their compute and model tokens without you handing out anything:
- They bring their own agent. A contributor runs one command on their laptop, cluster, or Compose box; it connects outbound to your hive, takes one curated task at a time, and runs their CLI with their model and their subscription.
- Their secrets never reach you. API keys and CLI logins stay on the contributor's machine. The hive never sees them.
- Your forge settings never change. Nobody is added as a collaborator. For each task the hive mints a short-lived, task-scoped GitHub token so the PR can be opened, then it expires. Revoke a contributor and their access is gone.
- Your prompts, your limits. Contributors work the queue you curated, under the same trust level, filters and gates as your resident agents.
The result is an elastic swarm: a three-person project can have a dozen contributors' agents grinding its backlog overnight, each accountable to a named human, while the maintainers hold every merge decision. See src/docs/contributor-relay.md.
- Hive the project: Apache-2.0 code in this repo. Run it yourself.
- Hive the hosted service: hive.hivecommons.dev — a hub we operate so you can onboard a spoke without a cluster. Same software, one deployment of it.
Do I need a paid agent subscription? No. Hive drives the agent CLIs you already have (Claude, Copilot, Codex, Antigravity, Goose) or any OpenAI-compatible model through its Model Gateway (OpenRouter key, no CLI login). Contributors can bring their own.
Who tells it what to work on? Your backlog does. The Governor reads your issues/PRs/CI, filters them deterministically (labels, areas, complexity), and only hands agents work you have allowed. You choose the areas and the trust level. Nothing is invented.
We require design discussion before non-trivial PRs. That is a trust level, not a workaround: Measured mode = agents may only file findings and proposals as issues — no code, no PRs — so the discussion happens first; Holdgated = PRs are opened with a hold label and a human must review and release; Full (L6) = merge on green. Start at Measured. You never have to move up.
Can it open PRs to our upstream repo? Yes, if you install it there. Or run it on a fork (upstream_watch keeps the fork current) and push reviewed PRs upstream yourself.
More answers: https://docs.hivecommons.dev/docs/community/what-is-hive-commons#does-hive-fit-my-project
| Path | Start here |
|---|---|
| Docker Compose | Quick Start (Docker Compose) |
| Podman | Quick Start (Podman) |
| Kubernetes | Kubernetes deployment |
| Hosted hub | https://hive.hivecommons.dev and the hosted hub guide |
| Getting started | Zero to Automation: Getting Started with Hive |
Configuration lives in hive.yaml; see the operator reference, environment variable reference, and agent configuration.
Hive uses an AI Codebase Maturity Model (ACMM) with six levels that control what agents are allowed to do:
| Level | Name | What agents can do |
|---|---|---|
| L1 | Inception (Assisted) | Interactive advisor and project inception. Advisory beads only. |
| L2 | Advisory (Instructed) | Observe and report findings as dashboard beads. No GitHub interaction. |
| L3 | Quality-Gated (Measured) | Quality agent opens issues and PRs gated by the literal hold level-gate label. Others remain advisory. |
| L4 | Security-Aware (Adaptive) | All agents file issues. Quality, sec-check, and CI open PRs gated by hold. |
| L5 | Semi-Autonomous (Semi-Automated) | All agents open PRs gated by hold. Humans batch-review and approve. |
| L6 | Fully Autonomous | Agents open PRs and auto-merge when checks pass. Non-outreach PRs have no level hold; outreach PRs remain held. |
See src/docs/acmm-policy-matrix.md for the full matrix and src/docs/labels-and-control-signals.md for label behavior.
Hive runs as a single container with a Go control plane, an authenticated Node.js gateway, and ttyd for web terminal access. The Governor evaluates queue depth, deterministic filters decide what an agent may see, scoped tokens and a MITM proxy enforce what it may do, and gates decide what may land.
See src/docs/architecture.md for process model, governor loop, guardrails, hub/spoke, and walkthrough diagrams.
hivectl tui is a full-screen terminal view of the same dashboard API the web UI uses: agents, governor, token spend, live activity, pause/resume, kick, ACMM level, and hive-profile actions.
See hivectl tui in the command reference.
Community members can contribute compute to any hive through ClankeR, the contributor relay (see above): it hands tasks from a hive's backlog to the CLI agent running on your own machine, under the hive's prompts and limits, with no repo permissions and no shared secrets.
Start with src/docs/contributor-relay.md or the Hive Hub contribute page.
Homebrew is an additional install option:
brew install hivecommons/hive/contributeFollow the Homebrew setup instructions
to register without a checkout before running hive-contribute. The
just workflow remains the
from-source path.
Moved to Quick Start (Docker Compose), Quick Start (Podman), and Kubernetes deployment.
Moved to src/docs/quickstart-docker-compose.md.
Moved to src/docs/quickstart-podman.md.
Moved to src/docs/kubernetes-deployment.md.
- Goose, an agent backend whose upstream moved to the Agentic AI Foundation (AAIF). Hive integrates Goose as an independent CNCF project; Hive does not join AAIF, seek AAIF membership, or rely on AAIF to host or govern Hive. See unattended Goose with Hive and Goose upstream tracking.
Hive is one of several repositories in the hivecommons organization. See docs/repositories.md for the full list, what each one is for, and which ones ship inside a Hive release.
See the Hive Hub to browse registered hives, view leaderboards, and find hives accepting contributions.
To contribute to Hive itself, see CONTRIBUTING.md and open issues or PRs on this repository. Contributors are expected to follow the CNCF Code of Conduct, adopted in CODE_OF_CONDUCT.md.
Recent user-visible changes are recorded in CHANGELOG.md.
For a code-grounded inventory of agent safety controls, enforcing versus advisory modes, known gaps, and running-hive audit steps, see the Security Model.
Please see SECURITY.md for the vulnerability disclosure process. Data collection and telemetry paths are documented in src/docs/telemetry.md. Do not report security vulnerabilities through public issues or pull requests.
Apache 2.0
Hive is a Cloud Native Computing Foundation sandbox project candidate; onboarding status is tracked in src/docs/cncf-sandbox-onboarding.md. This does not imply CNCF acceptance or endorsement. Copyright The Linux Foundation and Hive contributors. The Linux Foundation has registered trademarks and uses trademarks. For a list of trademarks of The Linux Foundation, please see the Linux Foundation Trademark Usage page. Hive project names and logos are used in accordance with that policy once ownership is transferred to the Linux Foundation/CNCF.