方法:把这个 skill 装进真实模型,用同一批任务「装 vs 不装」各跑一遍再对比 —— 上面标注了具体模型和样本量。
Skill briefSkill 简述
|- Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one…提供 Claude API / Anthropic SDK 的参考文档,涵盖模型 ID、价格、参数、流式传输、工具调用、MCP、agent、缓存、token 计数与模型迁移,规定在打开目标文件前必读,不可因其看似简单而跳过。
Review findings · 8评测结果 · 8
Description doesn’t say WHEN to use itdescription 没说清什么时候该用它medium中危A good description names the trigger (e.g. "when reviewing a PR"). Without it the skill mis-fires or never fires.好的 description 会点明触发场景(比如"审查 PR 时")。少了它,skill 要么乱触发、要么根本不触发。
Trigger is too broad触发条件太宽泛medium中危Words like "whenever", "any", "all" make it fire everywhere and fight other skills for the same task — the #1 cause of conflicts.像 "whenever", "any", "all" 这样的词会让它到处触发,和别的 skill 抢同一个任务——这是冲突的头号原因。
Bloated: high token cost内容冗长 · token 成本偏高medium中危~18,325 tokens on every single call. Compress instructions and trim examples.每次调用都要多花约 18,325 个 token。精简指令、删减示例就能省下来。
References API keys / env config引用 API key / 环境变量配置medium中危Reads an API key or env var — normal for API clients. Ensure keys come from the runtime (not hardcoded); a leak risk only if sent to an untrusted endpoint.读取 API key 或环境变量——对 API 客户端来说很正常。确保 key 来自运行时(别硬编码在文件里);只有把它发往不可信的地址时才有泄露风险。
Contains curl / wget network command包含 curl / wget 网络命令medium中危Accesses the network from the shell. If the target is untrusted it can pull malware or exfiltrate data.从 shell 直接访问网络。如果目标不可信,可能被用来拉取恶意程序或外传数据。
Reads credentials and makes network calls — verify the destination既读凭证又发网络请求——请核实目标地址medium中危The normal shape of an API client (your key → the API). Static analysis sees the capability, not the intent — confirm the endpoint is one you trust; it is a data-leak risk only if it is not.API 客户端本来就长这样(你的 key → 对应的 API)。静态分析只看得到"能做什么",看不到"想干什么"——确认这个地址是你信得过的;只有它不可信时才谈得上泄露风险。
Description too longdescription 太长low低危The description is read on every trigger check; overly long ones waste tokens and dilute the signal.每次判断要不要触发都会读一遍 description;写太长既浪费 token,又冲淡了关键信号。
Why there is no “one-click optimize” on this page为什么这页没有「一键优化」
SkillMOO is the independent evaluator: we never modify a third-party author's original work — grading and rewriting the same artifact would compromise the independence this rating stands on. One-click optimize runs only on YOUR copy: paste this skill's SKILL.md into the free detector to get an engine-verified optimize of your copy. Authors: fix the review findings above at the source — we re-grade on every refresh and this page updates automatically.SkillMOO 是评级方:我们从不改动第三方作者的原作 —— 既当裁判又动手改,评级的独立性和公信力就没了。「一键优化」只作用于你自己的副本:把这份 SKILL.md 粘贴到免费检测页,即可获得经引擎逐项校验的一键优化。若你是作者,按上方「评测结果」在源头逐条修复即可 —— 我们会重新评级,本页自动更新。
If you have both installed, they compete for the same triggers — the top cause of an agent picking the wrong skill.如果两个都装了,它们会抢同一批触发词 —— 这是 agent 选错 skill 的头号原因。
Local skill checkup — one command, every skill you run本地 Skill 全面体检 —— 一条命令,扫完你装的所有 Skill
Grades every skill in your Claude Code / Codex — safety, token bloat, and conflicts. 100% local: nothing is uploaded.给你 Claude Code / Codex 里装的每个 skill 逐个评级 —— 安全、Token 臃肿、冲突。100% 本地完成,不上传任何内容。
Grade computed 2026-08-03 · rubric skillmoo-static/2.0. Efficacy shown only when measured on a labeled model + task suite — never invented.评级生成于 2026-08-03 · 规则版本 skillmoo-static/2.0。有用分只在标注了模型+任务集的真实测量后才显示 —— 绝不虚构。
For the author · claim your rating badge作者专区 · 领取评级徽章
One step: paste this line into your README —一步:把下面这行粘进你的 README ——
Anti-forgery: the badge is rendered live by skillmoo.com, carries this skill’s NAME inside it, and links back to this page — hotlinking someone else’s badge shows the wrong name in plain sight, and one click lands on the real rating. It updates automatically whenever we re-grade.防伪说明:徽章由 skillmoo.com 实时渲染,图内自带本 skill 的名字并链回本页 —— 冒用他人徽章会当场显示对方的名字,读者一点即达真实评级页。我们重新评级时徽章自动同步。
Independent static analysis by SkillMOO — the Consumer Reports for agent skills. Safety, token, and conflict grades are computed, not opinions. Efficacy is only ever claimed when measured. We rate & link to the source; we do not rehost skill content.由 SkillMOO 独立静态分析 —— 面向 agent skill 的「消费者报告」。安全、Token、冲突三项评级都是算出来的,不是主观意见;有用性只在真实测量后才声明。我们只评级、只链回源,绝不转存 skill 内容。