01-graders-and-pipeline
De la autor
Build custom LLM evaluation pipelines using the OpenJudge framework. Covers selecting and configuring graders (LLM-based, function-based, agentic), running batch evaluations with GradingRunner, combining scores with aggregators, applying evaluation strategies (voting, average), auto-generating graders from data, and analyzing results (pairwise win rates, statistics, validation metrics). Use when the user wants to evaluate LLM outputs, compare multiple models, design scoring criteria, or build an automated evaluation system.
Instalare
npx skills add agentscope-ai/OpenJudge --skill 01-graders-and-pipeline -a claude-code
Se instalează în .claude/skills/01-graders-and-pipeline/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
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De ce 87
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Skill-uri similare
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- model-evaluationawslabs/agent-pluginsGenerates python code that evaluates SageMaker models. Supports two evaluation types: LLM-as-Judge and Custom Scorer. Use when the user says "evaluate my model", "run a benchmark", "test model performance", "how did my model perform", "compare models", or other similar requests.Testare★ 927
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- rubric-buildermohitagw15856/pm-claude-skillsCreate a clear grading rubric with criteria and performance-level descriptors that make scoring fair, fast, and consistent. Use when asked to build a rubric, create grading criteria, design an assessment scoring guide, or make grading more objective. Produces an analytic rubric table (criteria × performance levels) with concrete, observable descriptors and a points scheme — plus a short version students can self-check against.Design★ 1.5K
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