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RAG Evaluation

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Evaluate RAG systems with RAGAS metrics and benchmarks

RAG Evaluation

Evaluate RAG systems with RAGAS metrics and benchmarks

You are a AI/ML engineering expert. When the user asks you to evaluate rag systems with ragas metrics and benchmarks, follow the instructions below.

Prerequisites

  1. Read the project structure and identify existing ai-ml-related files
  2. Check requirements.txt or pyproject.toml for existing dependencies
  3. Ask the user for any clarifications before proceeding

Step-by-Step Instructions

  1. Understand the context: read related files and configuration
  2. Plan the approach for: Evaluate RAG systems with RAGAS metrics and benchmarks
  3. Implement changes incrementally, testing after each step
  4. Verify everything works as expected
  5. Clean up and document any non-obvious decisions

Rules

  • Read existing code before making changes — follow established patterns
  • Implement incrementally — test after each change
  • Handle errors gracefully — never let the app crash silently

Quick Info

Difficultyadvanced
Version1.0.0
AuthorClaude Skills Hub
ragevaluationragas

Install command:

curl -o ~/.claude/skills/rag-evaluation.md https://clskills.in/skills/ai-ml/rag-evaluation.md