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Community / AGENT SKILL
swarm
0
Fan out N parallel workers, drain them, and return one report. Use for $swarm, 'swarm this', or parallel coverage, races, gauntlets, and exploration.
Understand the trade-offs.
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How clearly the skill guides your agent, how complete its workflow is, and how you can check the outcome.
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The full skill.
Original instructions from the publisher’s SKILL.md
# Swarm Fan out N parallel cloud workers. They may cover separate slices, race the same brief, or mix both. The parent waits, aggregates, and returns one report. ## Start Open a todolist with one entry per phase before launching anything. 1. Frame 2. Fan out 3. Aggregate 4. Report ## Phase A: Frame 1. State the done predicate and the artifact or report the swarm must return. 2. Choose the shape. Partition into slices, race N workers on identical briefs, or mix both. For a race or mixed shape, declare `first pass`, `rank all`, or `best-of` before spawning. 3. Set N from the user or derive it from the shape. N is total workers, not the cloud concurrency limit. 4. Pick the worker model from `swarm workers` in `~/.codex/pstack-models.md` when present. Otherwise use `auto`. For a model race, name each arm's model up front. 5. Give each worker its own writable output when it writes. Use a worktree, branch, or `/tmp/swarm-<slug>/worker-<n>/`. ## Phase B: Fan out Spawn all N workers in one message with `a general-purpose subagent`, background execution, `run_in_background: true`, and the configured model. Use the host's local execution mode only when the worker needs access to something on the user's computer. When a worker must start from a non-default pushed branch, pass `cloud_base_branch`. Every brief stands alone. Include the goal, scope, exact slice or race arm, how to verify, and what to report. Reports use `PASS`, `ISSUES`, or `BLOCKED` with evidence. If a worker drops out, proceed with N-1 and note it. ## Phase C: Aggregate Read the terminal results. For coverage, every required slice needs a result. For a race, apply the selection rule declared up front. Use first pass, rank all, or best-of. Do not paste raw worker dumps. Keep a compact result table, one-line evidenced issues, and explicit gaps or dropouts. ## Phase D: Report Return one consolidated in-chat report with the table, issue one-liners, gaps or dropouts, and the race rule when used.
Skill folder
Files included alongside SKILL.md in the publisher’s repository.