Design rubrics, test cases, and metrics for AI model evaluations.
npx skills add https://github.com/RefoundAI/lenny-skills --skill ai-evals-refoundai
Please help me install this Agent Skill. Skill: ai-evals Source: https://github.com/RefoundAI/lenny-skills/tree/main/skills/ai-evals Command: npx skills add https://github.com/RefoundAI/lenny-skills --skill ai-evals-refoundai
AI evaluations are often ad hoc, leading to inconsistent conclusions across features and teams. This Skill helps product teams design repeatable, measurable evaluations that align with user needs and business goals.
Design a complete AI evaluation plan for a chatbot feature by outlining rubrics, test cases, and scoring criteria.
High-intent search queries and answers about installing and using this skill.
To design repeatable AI evaluations, create structured rubrics that reflect real user outcomes, generate representative test cases, and define measurable metrics to assess LLM performance consistently across releases.
Writing rubrics for benchmarking LLM models involves creating specific scoring criteria that align with your product's user needs and business goals, ensuring model behavior is measured against expected real-world outcomes.
Generate test cases for AI product management by producing representative prompts and diverse scenarios that validate how the LLM-powered feature behaves under expected user interactions and edge cases.
Yes, you can measure and iterate on LLM performance by defining specific metrics, collecting evaluation results from your test cases, and using those data points to drive continuous improvement across feature releases.
Ad hoc AI evaluations lack structured scoring criteria and standardized test cases, causing inconsistent conclusions. A repeatable framework with defined rubrics and metrics ensures measurable alignment with user needs across teams.
When running AI evals for a chatbot, collect metrics derived from your predefined rubrics and test case results to quantify model performance, validate behavior, and identify areas for iteration.
kevinlinGenerate a structured PRD with problem statements, goals, user stories, and acceptance criteria.
tblakex01Benchmark the same prompt across Claude, GPT, and Gemini for latency, tokens, and cost.
KsawyouxEvaluate, version, and A/B test AI prompts against defined test cases.
mneves75Apply Test-Driven Development to create and test AI skills.
