사용 방법
- 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
- 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
- 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/aicodeking/deepseek-stack --skill ds-best-of-n시작 전 확인
- 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
- 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서
원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.
ds-best-of-n
One attempt is a sample, not an answer. DeepSeek is cheap enough that three to five attempts usually cost less than one round of fixing a bad first try.
Steps
- Frame the task. Write one prompt that every attempt gets unchanged. Write a private rubric of 3 to 6 concrete, checkable criteria. Attempts never see the rubric.
- Pick N. Use 3 by default and 5 when the design space is wide. Give each attempt its own output location, such as a git worktree or a separate temp folder.
- Spawn N subagents at once with the prompt, the shared context and their output path. Ask each for the artifact plus a short note on alternatives it rejected. If a harness cannot run subagents, run the attempts one after another in fresh contexts.
- Check each attempt. Run its build, tests or a quick probe. Record pass or fail with output. Discard attempts that do not run.
- Score the survivors against the rubric. Pick the one with the best overall structure as the base. Structure beats polish.
- List the specific strong parts of the other attempts: a test, an edge case, a cleaner function. Graft only those into the base. Do not merge whole files.
- Re-run the full checks on the grafted result and show the output.
Stop when
- The grafted result passes every check and you have reported base, grafts and scores.
- Or no attempt passes after one re-run with a clarified prompt. Report what failed.
Rules
- Never pick by reading the attempt's own summary. Pick by running it.
- Do not let one attempt see another before scoring.
- Keep the losing attempts until the final checks pass.
