使い方
- インストールコマンドをコピーし、自分の環境へ導入する前にソースを確認します。
- 必要なツール、認証情報、対応環境を原文で確認します。
- 入力と成果物を指定し、出力を資料と照合します。
npx skills add https://github.com/aicodeking/deepseek-stack --skill ds-best-of-n開始前の確認
- 導入にはモデル契約、API枠、ファイルへのアクセス許可は含まれません。
- スター数や導入数は活動の指標であり、独立した品質・安全性試験ではありません。
リポジトリの原文
見出し、例、コード、表、リンク、参照画像を含む原文を表示しています。
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.
