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/gnibu/bento --skill bento-hillclimb시작 전 확인
- 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
- 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.
Hillclimb
The failure mode: change three things at once, the number moves, you don't know which tweak did it — or whether it was noise. Next week it drops and you can't retrace. One variable at a time, logged, keep-or-revert.
Repo layer first. Read the repo's AGENTS.md/CLAUDE.md and, if it exists, the overlay .agents/bento/bento-hillclimb.md at the repo root; follow it under the overlay rules.
Steps (paste as todos)
- Freeze the harness first. Fix the dataset, the metric, and how it's measured
before touching the thing you're tuning. If the ruler moves, no result means anything.
- Record the baseline. Run the frozen harness once. Write the number down.
- Change ONE variable. One knob per experiment. Never stack untested changes.
- Measure against baseline. Same harness, same input set.
- Keep or revert — and log it either way. Keep only a real gain (significant, not
noise; re-run if the sample is small). Log the attempt, the delta, and the decision. A reverted attempt is still knowledge — write it down so you don't retry it.
- New baseline on a keeper, then back to step 3.
- Don't stop on a lucky first hit. Run enough iterations that one good roll can't
fool you. State the stop condition up front (target metric, or N no-improvement rounds).
Guardrails
- Regression check on every keeper: a gain that breaks something else is not a gain.
- If two knobs seem coupled, that's a finding — still change one, note the interaction.
- The log is the deliverable as much as the final number. No log = you learned nothing
transferable.
