使用方法
- 复制安装命令，在自己的智能体环境安装前先检查源码包。
- 从原始文档核对所需工具、凭据和支持的宿主。
- 说明输入材料与期望交付物，并对照来源检查输出。
npx skills add https://github.com/ai-evals-course/evals-skills --skill evals-start开始前需了解
- 安装不包含模型订阅、API 额度或访问文件的权限。
- 仓库星数和安装量反映活跃情况，不等于独立质量或安全测试。
仓库原始内容
按源仓库内容呈现，保留标题、案例、代码、表格、链接以及原文引用的演示图片。
Evals Start
This plugin splits eval work into targeted skills. Your job here is small: find the row below that matches the user's situation, tell the user which skill you are loading and why, then load that skill and follow its workflow from start to finish instead of improvising your own version of it.
| Situation | Skill to load |
|---|---|
| Has traces, wants to find failure modes, no established taxonomy yet | error-discovery |
| Has an existing eval pipeline and wants to know if it can be trusted | eval-audit |
| Has a known failure mode that code can check (e.g., format, schema, regex, execution) | write-code-eval |
| Has a known failure mode and wants an LLM judge for it | write-judge-prompt |
| Has an LLM judge or evaluator and wants to check its quality | validate-evaluator |
| Has no traces to review yet | generate-synthetic-data, then error-discovery |
| Wants a custom annotation interface for some other labeling task | build-review-interface |
| Wants to evaluate a RAG pipeline | evaluate-rag |
Most requests that mention error analysis with traces in hand mean error-discovery. New users with an existing pipeline usually need eval-audit first. This file holds only routing. When in doubt about which row fits, ask the user instead of guessing. The workflow lives in the targeted skill.
