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.
- Frame
- Fan out
- Aggregate
- Report
Phase A: Frame
- State the done predicate and the artifact or report the swarm must return.
- 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.
- Set N from the user or derive it from the shape. N is total workers, not the cloud concurrency limit.
- Workers inherit the session model by default. Pass
model on the Agent call only when a cheaper tier clearly fits mechanical work, or when the point is a model race, in which case name each arm's model up front.
- 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 the Agent tool, subagent_type: general-purpose, and isolation: "worktree" for every worker that writes, so their edits cannot collide. Inside a Rove session ($ROVE_TASK_ID set), workers that edit files are Rove tasks instead — rove api add --count N, or one add per slice (see the rove skill) — so the user can see and steer them.
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.