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meta-eval

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Use when the user wants to build an evaluation system for an LLM/agent application but doesn't know where to start — they have traces, prompts, RAG pipelines, or nothing at all. Also use when the user mentions evaluation, eval, benchmarking, testing LLM quality, measuring agent performance, assessing RAG accuracy, or wants to compare prompts/models. This skill is the entry router: it asks diagnostic questions then recommends which sub-skill (local workflow) to use next.

skills/eval_pipeline/00-meta-eval/SKILL.md

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Nov 9, 2026
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Apache-2.0

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<HARD-GATE>
NO sub-skill recommendation WITHOUT identifying data_form + label_status (these two pick the entry workflow).
ALWAYS give a provisional recommendation once data_form + label_status are known, even if stakes/user_prior are still unknown — then ask the remaining questions to refine the downstream path. Do not withhold the route while waiting on stakes.
</HARD-GATE>

# Meta Eval

Entry router for the eval skill collection. You diagnose what the user has and route
them to the right sub-skill. You don't do evaluation yourself — you're the triage desk.

Each sub-skill is self-contained: it carries inline the data shapes, statistics, and data
principles it needs, so it can be installed and used on its own.

## Checklist
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