AGENT SKILL

beads-coordinator

Coordinate unattended Beads issue execution — rank ready work finish-first (epics closest to done before new ones), claim atomically, and allocate cohesive delivery packages to persistent outcome owners, alone or as one of several coordinators sharing a backlog. Use for unattended issue throughput in Beads-backed repos.

License 许可
MIT
最近更新
2026-11-10
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01 前言 Front Matter

name
beads-coordinator
metadata
{ "owner": "tze", "status": "active", "authors": [ "tze", "OpenAI Codex", "Claude Fable 5.1", "Claude Opus 5.5" ], "last_reviewed": "2026-11-06" }
description
Coordinate unattended Beads issue execution — rank ready work finish-first (epics closest to done before new ones), claim atomically, and allocate cohesive delivery packages to persistent outcome owners, alone or as one of several coordinators sharing a backlog. Use for unattended issue throughput in Beads-backed repos.
compatibility
Requires a Beads-backed repository with `bd` v1.3+ (`parent` on list rows, `bd epic status`, `--if-assignee`), `uv`, `git`, an authenticated `gh`, `jq`, git worktree support, and network access for `gh` PR operations.

02 资源文件 14

03 SKILL.md 正文

Beads Coordinator

Allocate bounded outcomes to persistent implementation owners and recover their delivery. This controller handles lifecycle writes for dispatched workers; implementation, diagnosis and routine corrections remain with the same owner. For a session doing its own delivery use beads-looper. For a supplied package use beads-worker.

Use for “keep N workers finishing the backlog”, “finish started outcomes first”, or “coordinate several owners on this tracker”. Backlog authoring routes to beads-writer, recovery-only to beads-cleanup.

Contract and reading order

  1. Shared delivery model: units, persistent owners, branch tradeoffs, packets, claim journal, evidence and acceptance.
  2. Coordinator loop: allocation, review wiring, corrections, landing, per-member reconciliation and reports. Start here after the shared model; load other references only for the step that needs them.
  3. Runtime and safety: actor/lease, capacity, guarded adoption, model selection and bounded waits.
  4. Epic coordination: shared prerequisites and finite programme ownership; no extra mini-coordinator tier.
  5. Commands: CLI lookup and session completion.

Claim with atomic --claim, use a unique actor and never mutate another live actor's claims. Multi-bead packages use the shared helper and journal. Dispatch native runtime sessions with absolute skill paths and concise current packet locators. Require worker bootstrap proof before editing. Never commit Dolt-managed .beads/ files, run production actions without authority, or bypass a repo gate.

Executable consumers

  • rank_ready_work.py ranks finite outcomes and prerequisites and review-first admission. Pass the Step 0 normalization file; queue is executable order, candidates diagnostic only. Missing review evidence dispatches nothing; parked owners keep claims without consuming execution slots.
  • coordinator_registry.py is the registry writer and shared liveness reader; do not hand-write registry expiries.
  • normalize_pr_review_state.py reports canonical anchor/review associations and terminal-state recommendations.
  • review_relation_graph.py validates relations without I/O; partial relation/inventory evidence permits no mutation.

Target trackers using bd -C /absolute/repo on every command when outside that repo. A bead prefix does not route across databases. Search known errors for unexpected errors, append confirmed new fixes there, and apply decision autonomy when a blocker is actually an engineering choice. Use token efficiency for projected output and reuse of evidence rather than repeated full scans.

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开发工程师代码审查
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Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

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