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SwarmForge: Open-source tool for coordinating multiple AI agents

SwarmForge: Open-source tool for coordinating multiple AI agents

Key takeaway

  • SwarmForge is an open-source, locally-run orchestration system that lets multiple AI agents collaborate on software engineering projects.

  • It uses tmux and git to coordinate specialized agent roles (such as coder, architect, and QA), manage separate code branches via worktrees, and pass work between agents through a validated handoff protocol.

  • Three pre-built workflow templates—two-pack, four-pack, and six-pack—scale from small tasks to major projects, each with different numbers of agent roles and quality gates.

3 Key Points

  1. What happened

    An open-source project called SwarmForge has been released on GitHub (at github.com/unclebob/swarm-forge) as a tmux-based orchestration platform for coordinating multiple AI agents working together on software engineering tasks. It offers three pre-built workflows (two-pack, four-pack, and six-pack) with 2, 4, and 6 agent roles respectively, each optimized for different project sizes and complexity levels.

  2. Why it matters

    Teams using AI agents for development can now coordinate multiple specialized agents (coder, architect, QA, etc.) working in parallel on the same project without stepping on each other's work. SwarmForge handles role assignment, git worktree management, message passing, and backend selection (Claude, Copilot, Codex, or Grok), turning what would be manual coordination into a structured, repeatable workflow.

  3. What to watch

    SwarmForge runs entirely locally using tmux and git, requiring only zsh, git, tmux, Babashka, and at least one configured agent backend. Users can start with the quick two-agent workflow, move to the moderate four-agent specification workflow, or use the full six-agent workflow for major projects. The system includes a layered constitution structure that allows project-specific customization while maintaining shared operational scripts.

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Context & Analysis

SwarmForge addresses a practical gap in AI agent coordination: while individual agents can write or review code, orchestrating multiple specialized agents without manual handoff work has been cumbersome. The project's three templated workflows (two-pack, four-pack, six-pack) reflect a deliberate design choice to match scope to complexity—small tasks can use a lean two-agent setup, while major projects benefit from full separation of concerns across six roles (specifier, coder, cleaner, architect, hardener, QA). By running entirely in tmux and git on a local machine, SwarmForge avoids external dependencies and keeps all swarm state contained in the project directory (.swarmforge/), making it portable and self-contained. The layered constitution system—where shared default articles live on main and runnable branches can add or override them—allows teams to maintain consistent engineering standards while customizing workflows per project. The validated handoff protocol (enforcing exactly 10-character commit abbreviations and single-line message limits) is designed to prevent silent failures and keep agent communication reliable and auditable.

FAQ

What are the three workflow options, and when should I use each?
Two-pack is the quick workflow for small tasks with a coder and cleaner agent, optimized for fast coding without specification overhead. Four-pack is the compact specification workflow for moderate projects with a specifier, coder, refactorer, and architect. Six-pack is the full workflow for major projects, adding dedicated cleaner, hardener, and QA roles to separate each quality gate into its own agent.
What agent backends does SwarmForge support?
SwarmForge supports Claude, Codex, Copilot, and Grok as configured agent backends. Each role in a workflow can be assigned a different backend.
How do agents communicate with each other while working?
Agents communicate through validated handoff files managed by a daemon (handoffd.bb). Agents create outbound handoffs using swarm_handoff.sh (which supports git handoffs pointing to committed states or short freeform notes), accept work with ready_for_next.sh, and complete work with done_with_current.sh. The daemon watches agent outboxes, validates handoff files, and copies them into recipient inboxes.

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