best-of-n-parallel-attempts

name	Best of N (parallel attempts)
description	Delegate N parallel subagents on the same task, then pick the best result.
triggers	["best of n","parallel attempts","explore options","try variants","best-of-n"]

Best of N (parallel attempts)

Use this when a task has a wide solution space and you want the strongest result: run N independent attempts in parallel and choose the best. Each attempt is isolated, so they cannot interfere with each other.

Steps

1. Pick N. Default N = 3 (cap to the parallelism limit). For a code task use the implementer role; for analysis/design use researcher or design-doc-writer.
2. Fan out. delegate N subagents with the same task in a single delegate call so they run in parallel. Give each identical, complete instructions.
3. Compare. When the summaries return, evaluate each against the goal and the acceptance criteria (correctness, simplicity, completeness, risk).
4. Choose. Pick the best attempt. The others' isolated copies are simply rejected at merge time (not applied).
5. Summarize. State which attempt you chose and why, and what is staged for merge.

Notes

• The attempts are blind to each other — that is the point (diversity).
• Vary the instruction slightly per attempt only if you want different angles; otherwise keep them identical for a fair comparison.
• Only the chosen attempt's changes should be merged; explicitly discard the rest.