best-of-n
GitHub用于高价值或模糊任务的多方案并行生成与评估。通过独立工作树生成候选解,基于明确标准进行裁判打分,验证后应用最优结果,提升决策质量。
Trigger Scenarios
Install
npx skills add Hmbown/CodeWhale --skill best-of-n -g -y
SKILL.md
Frontmatter
{
"name": "best-of-n",
"metadata": {
"short-description": "Compare independent candidates"
},
"description": "Generate a small set of independent candidate solutions in worktrees, judge them against one explicit rubric, and apply the winner only after PASS verification."
}
Best of N
Use this skill when a consequential design, implementation, explanation, or debugging task has several plausible solutions and comparison is worth the extra model work. In Operate mode this is the preferred ensemble pattern for high-stakes or ambiguous approaches. Do not use it for a tiny change or when the user has already chosen the approach.
Set The Tournament
- Define one task, one evidence packet, and one explicit scoring rubric before launching candidates. Include correctness, fit to the request, simplicity, risk, and verification.
- Choose
Nfrom 2 to 4 for a quick comparison (default 3). For an explicit experimental search, use the Workflow search option: 2–16 live candidates, with larger validated populations queued at the Workflow host's 16-worker concurrency gate rather than launched at once. - Give every candidate the same task and rubric. Add only a candidate number; do not steer candidates toward different conclusions unless diversity is an explicit part of the request.
- Prefer a session goal (
create_goalor active/goal) when the tournament spans more than one parent turn.
Generate Independently
Start the candidates as parallel background agent workers and return agent_ids
immediately so the parent stays free. For proposals, reviews, or research, keep
them read-only:
{
"action": "start",
"name": "candidate_1",
"prompt": "Produce candidate 1 for the task below. Return the proposal, evidence, risks, and rubric self-score. Do not edit files.\n\n<TASK AND RUBRIC>",
"type": "worker",
"model_strength": "same",
"write_authority": "read_only"
}
Launch the remaining candidates with the same contract, then use agent wait
or completion events to collect every result. Do not show one candidate another
candidate's answer before generation finishes.
When candidates must implement code, give each one:
type: "builder"worktree: truewrite_authority: "worktree_write"- the same bounded
write_rootsorexact_files
Never run parallel writers in the parent checkout. Each builder must return the structured candidate contract (candidate id, hypothesis, paths, commands, self-verdict, risks, and artifact references). A self-verdict is evidence to inspect, not a hard-gate result.
Optional diversity: pin different model / Fleet fleet_profile values when
the project has multiple capable routes; otherwise keep model strength same.
Judge Once
Use one read-only reviewer worker, or the parent when the result is small, to score all candidates against the original rubric. The judge must:
- cite evidence from each candidate rather than vote by style;
- reject candidates that violate authority, scope, or verification gates;
- treat candidate-reported commands and PASS claims as untrusted until replay;
- name the winner and the decisive reasons;
- identify useful pieces worth combining, if any;
- say when the candidates are tied or all fail.
Do not ask candidates to vote for themselves. Do not silently merge incompatible approaches into a new unreviewed solution.
Integrate Only After PASS
For proposal-only work, return the winning answer with a compact score summary. For code work:
- Freeze the baseline, evaluator, hard gates, score rule, and authority before a larger search admits candidates. Any evaluator change starts a revision.
- After a worker loses write authority, apply its patch to a clean baseline and let the runtime—not that worker—run hard gates and scoring.
- Inspect the winning worktree diff and independently replay it on the clean baseline. A different read-only model may look for gaming, but deterministic tests remain the authority.
- Present the verified winner for review. Applying or merging is a separate,
explicit user action;
NONEis valid when every candidate fails. - Preserve losing and failed candidate receipts as useful negative results.
The checked-in operate_best_of_n.workflow.js recipe supports
strategy: "search" for structured 2–16 candidate generation and review. It
does not yet turn prompt-listed commands into hidden runtime gates. Do not
advertise those gates until the runtime evaluator host consumes a frozen
WorkflowSearchSpec.
Stop early when one candidate reveals a hard constraint that invalidates the tournament. Report the negative result rather than spending the remaining budget to manufacture variety.
Version History
-
0fe366b
Current 2026-08-16 09:02
修复提示词中使用的已废弃工具名称(如read_file),替换为正确的内部调度键(如File read),防止模型因无效工具名导致执行失败。
- b0e4926 2026-07-24 17:42


