菜单
Check whether a CV-CUDA operator is READY to optimize (correctness + bench coverage + captured baseline + profiling) per .agents/guidance/OPTIMIZATION_GUIDELINES.md. Use before starting an optimization campaign to confirm the readiness gate is clean.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/CVCUDA/CV-CUDA --skill optimize-op-preflight命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | optimize-op-preflight |
| description | Check whether a CV-CUDA operator is READY to optimize (correctness + bench coverage + captured baseline + profiling) per .agents/guidance/OPTIMIZATION_GUIDELINES.md. Use before starting an optimization campaign to confirm the readiness gate is clean. |
Thin entry point. Run python3 tools/optimize_op.py <Op> --phase preflight and interpret per
the tool's readiness (PRE-*) findings against .agents/guidance/OPTIMIZATION_GUIDELINES.md: correctness/regression coverage and
benchmark coverage (reused from review_op.py test+bench), a captured baseline, and profiling
tools. Any GAP means the operator is not ready — add the missing coverage first, in a
separate non-perf: commit, before starting the optimization. Resolve MANUAL items at the
cited locations. Findings-first.
