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.
How to install 00-meta-eval?
agentscope-ai/openjudge/00-meta-eval
$npx -y skills add agentscope-ai/openjudge --skill 00-meta-evalInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/agentscope-ai/openjudge" --skill "agentscope-ai/openjudge/00-meta-eval"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/agentscope-ai/openjudge" that are relevant to the current task. Run `npx skills add "https://github.com/agentscope-ai/openjudge"` and select the relevant skills, then follow their instructions.
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