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D

claude-api

by来自 anthropics/skills · view source ↗查看源 ↗
Autonomous Coding自主编程see source见源仓库18,325 tok/call18,325 token/次SKILLMOO D
Usable, but review first — and it is token-heavy能用,但先审一遍 —— 而且很吃 Token
40/100
Safety grade安全评级
D
40/100 · gate: review40/100 · 闸门:复核
Token costToken 成本
18,325
9.0× median9.0× 中位
Efficacy有用性
+33.3 pts
on older models · measured在 老模型 模型上 · 实测
Efficacy · actually measured (not guessed)

A real boost on standard / older models (+33.3); today's top models already have this built in.

Today's top models
This tier already does it — no lift to add · e.g. Claude 4 · GPT-4-class · DeepSeek-V3
100% without → 100% with · measured on deepseek-chat (4×5)
Standard / older models
Clearly better with it (+33.3 pts) · e.g. MiniMax-Text-01 · smaller open models
0% without → 33% with · measured on MiniMax-Text-01 (4×6) · 95% CI 14–52 pts
How: we install the skill into a real model, run the same tasks with it vs without, and compare — labeled with the exact model + sample size above.
有用性 · 真实测量(非猜测)

如果你用的是标准 / 较老的模型,这个技能帮大忙(+33.3);用主流强模型的话它已内置、基本用不上。

主流强模型
这类模型已自带,装不装一个样 · 如 Claude 4 · GPT-4 级 · DeepSeek-V3
不装 100% → 装上 100% · 实测于 deepseek-chat(4×5 次)
标准 / 较老模型
装上后明显更好(+33.3 分) · 如 MiniMax-Text-01 · 较小的开源模型
不装 0% → 装上 33% · 实测于 MiniMax-Text-01(4×6 次) · 95% 区间 14–52 分
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

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。

Optimize my copy →去优化我的副本 →

Conflicts with · 1与之冲突 · 1

cloudflare-email-serviceshadow遮蔽api, sdk, agent

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。

npx skillmoo scan

Browse all rated skills浏览全部评级 skill

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 ——

[![SkillMOO](https://skillmoo.com/badge/claude-api)](https://skillmoo.com/skill/claude-api/)

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.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。