Overview
Beads — the `bd` command — is a distributed graph issue tracker built for AI coding agents, powered by Dolt, the version-controlled SQL database. It exists to replace the sprawling markdown plan files agents tend to write with a dependency-aware graph, so a long-horizon task survives the end of a context window: work is created as beads, linked by dependencies, and `bd ready` returns exactly the tasks that have no open blockers.
The design targets multi-agent and multi-branch work. Hash-based IDs such as `bd-a1b2` avoid merge collisions when several agents create issues at once, Dolt supplies cell-level merge, native branching and sync through Dolt remotes, and `bd update --claim` atomically assigns a task and moves it to in-progress so two agents do not pick up the same work. Hierarchical IDs (`bd-a3f8`, `bd-a3f8.1`, `bd-a3f8.1.1`) express epics, tasks and sub-tasks; graph links (`relates-to`, `duplicates`, `supersedes`, `replies-to`) turn the tracker into a small knowledge graph.
Beads is a CLI you install once and use across projects — the README is explicit that you should not clone the repository into your own. `bd init` sets up a project, writes or updates `AGENTS.md` so agents discover the workflow, and installs integrations; `bd setup` covers Codex, Claude Code, Factory.ai Droid, Cursor, mux and others. Beyond tasks, `bd remember` stores durable project memory that `bd prime` injects back at session start, and compaction summarises old closed work so the context window stays lean. A stealth mode keeps everything local when you would rather not commit tracker files to a shared repo.
What it does
- Dolt-powered storage: a version-controlled SQL database with cell-level merge, native branching and sync over Dolt remotes
- Dependency graph with `bd ready` auto-detection of claimable, unblocked work, and atomic claiming via `bd update --claim`
- Hash-based IDs (`bd-a1b2`) so parallel agents and branches never collide on issue numbers
- Persistent project memory: `bd remember "insight"` stores it, `bd prime` injects it plus workflow context at session start
- Compaction — semantic memory decay that summarises old closed tasks to save context window
- One-command agent integration through `bd setup` for Codex, Claude Code, Factory, Cursor and more, plus an npm package and a `beads-mcp` PyPI package
Getting started
Beads is a system-wide CLI available for macOS, Linux, Windows and FreeBSD. Install it once, then initialise it inside each project you want tracked.
Install the CLI
Homebrew is the recommended route; an npm package and an install script are also published.
brew install beads
# or
npm install -g @beads/bdInitialise it in your project
Run `bd init` from your own repository — not from a clone of the Beads repo. It creates or updates AGENTS.md so agents discover the workflow, and installs project integrations unless you pass --skip-agents or --stealth.
cd your-project
bd initWire up your agent
Install richer instructions, hooks and skills for the agent you use. `bd setup --list` shows every supported integration.
bd setup claude # Claude Code — hooks/settings
bd setup codex # Codex CLI — skill, AGENTS.md guidance, hooks
bd setup factory # Factory.ai Droid — creates/updates AGENTS.mdWork the graph
Create tasks, link dependencies, and let the agent claim whatever is ready.
bd create "Title" -p 0
bd dep add <child> <parent>
bd ready
bd update <id> --claim
bd show <id>
bd close <id>Commands and code are distilled from the project's own documentation — always check the official repo for the latest.
When to use it
- Give a coding agent long-horizon work it can resume: a dependency graph of tasks instead of a markdown TODO that falls out of context
- Run several agents or branches against the same backlog without merge collisions on issue IDs
- Keep durable project decisions where the agent will actually see them, via `bd remember` and `bd prime`
- Track personal planning on a shared repository without committing tracker files, using `bd init --stealth`
How Beads compares
Beads alongside other open-source ai sdlc automation tools AI/TLDR tracks, ranked by GitHub stars.
| Tool | Stars | What it does |
|---|---|---|
| Multica | ★ 50.4k | Self-hostable workspace where coding agents are assigned issues like teammates: 26 agent CLIs, runtimes you own, a replayable execution log per run, and review gates before anything ships. |
| GPT-Pilot | ★ 33.7k | Autonomous AI developer that breaks down an app description into tasks, writes and runs code incrementally, and asks clarifying questions to produce a working production application. |
| oh-my-codex (OMX) | ★ 33.2k | A workflow layer for the OpenAI Codex CLI that adds agent teams, git-worktree isolation, hooks and HUDs behind a set of canonical plan, code-review and QA commands. |
| Vibe Kanban | ★ 28.1k | Vibe Kanban lets you plan tasks on a kanban board, run coding agents like Claude Code and Codex in isolated workspaces, then review their diffs and ship pull requests. |
| Beads | ★ 27.3k | A dependency-graph issue tracker coding agents can claim work from |
| Archon | ★ 23.5k | A workflow engine for AI coding agents: describe plan, implement, validate, review and PR phases as YAML, and every run repeats them in its own git worktree. |
| Keploy | ★ 18.5k | An API testing tool that records real traffic with eBPF — including database and queue calls — and replays it as deterministic tests and data mocks, with no SDK to import and no code changes. |
| Superset | ★ 14.4k | An agentic IDE for macOS that runs 100+ CLI coding agents in parallel, each in its own git worktree, with a built-in terminal, diff viewer, in-app browser and completion notifications. |