rag-evaluator
OfficialEvaluate RAG systems for groundedness, relevance, and quality.
AuthorGiskard-AI
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps you evaluate the quality of RAG (Retrieval-Augmented Generation) systems, ensuring groundedness, relevance, and overall quality of answers.
Core Features & Use Cases
- Groundedness Evaluation: Check if answers are supported by provided context.
- Answer Relevance: Ensure answers address the question correctly.
- Out-of-Scope Refusal: Verify that the system declines when it cannot answer.
- Retrieval Quality: Assess the quality of the retrieval system if one is exposed.
- Citation Accuracy: Check if citations are accurate and support the claims made.
- Use Case: When you have a RAG system and want to ensure it is providing high-quality, grounded answers that are relevant to the user's query.
Quick Start
Use the rag-evaluator skill to generate an evaluation suite for your RAG system. Provide information about your agent, KB, and any relevant data.
Dependency Matrix
Required Modules
giskard-checksgiskard.agentsgiskard.agents.generators
Components
scriptsreferencesassets
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: rag-evaluator Download link: https://github.com/Giskard-AI/giskard-skills/archive/main.zip#rag-evaluator Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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