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my-eval-plan
Design evaluation plans for AI/LLM features: datasets, scorers, baselines, success criteria, and regression strategy.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Design evaluation plans for AI/LLM features: datasets, scorers, baselines, success criteria, and regression strategy.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Address pending PR review feedback through verified triage, small fix phases, implementation, validation, and evidence-backed replies. Manual invocation only.
Autonomous iteration loop for a measurable goal: review, ideate, modify, verify, keep or rollback, repeat until interrupted or capped.
Monitor a PR's CircleCI pipeline, diagnose failures, apply scoped fixes, push when requested, and continue until green or blocked.
Stage and commit changes in logical groups using the project's git message style, without mixing unrelated user changes.
Create or update a GitHub PR with concise description, review guidance, triggered specialty reviews, and focus areas.
Build a daily work brief from yesterday/off-hours activity plus today's Linear, Calendar, Gmail, and Notion context; update Notion and produce standup/checklist.
| name | my-eval-plan |
| description | Design evaluation plans for AI/LLM features: datasets, scorers, baselines, success criteria, and regression strategy. |
Design a practical evaluation strategy before or alongside AI feature work.
Read ~/.claude/rules/question-policy.md when available. Use ~/.agents/rules/ under Codex. For full planning procedure, read references/protocol-index.md.
Return scorer definitions, dataset plan, baseline targets, instrumentation needs, and implementation checklist.