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Original

English

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Translation

Chinese

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开始

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 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.

本插件将评估工作拆分为多个针对性技能。你的任务很简单：找到下方与用户情况匹配的行，告知用户你将加载哪个技能及原因，然后加载该技能并全程遵循其工作流程，而非自行临时制定流程。

场景	需加载的技能
已有追踪数据，希望找出故障模式，尚未建立分类体系	`error-discovery`
已有评估流水线，希望确认其是否可信	`eval-audit`
已知故障模式，希望为此创建LLM评判器	`write-judge-prompt`
已有LLM评判器或评估器，希望检查其质量	`validate-evaluator`
暂无追踪数据可供分析	`generate-synthetic-data` ，随后加载 `error-discovery`
希望为其他标注任务创建自定义标注界面	`build-review-interface`
希望评估RAG流水线	`evaluate-rag`

大多数提及手持追踪数据进行错误分析的请求，都对应

error-discovery

技能。已有评估流水线的新用户通常首先需要

eval-audit

技能。本文件仅负责路由功能。若不确定哪一行匹配用户情况，请询问用户而非猜测。具体工作流程存在于对应的针对性技能中。