monitor-rag-quality
OfficialMeasure and monitor RAG pipeline quality for accurate context and answers.
AuthorContextJet-ai
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps diagnose issues in RAG (retrieval-augmented generation) pipelines, ensuring the correct context is retrieved and answers are faithful.
Core Features & Use Cases
- Quality Measurement: Evaluate the effectiveness of RAG pipelines using four key metrics: context precision, recall, faithfulness, and answer relevance.
- Diagnosis: Differentiate between retrieval and generation issues to apply appropriate fixes.
- Use Case: When encountering incorrect RAG answers, this Skill can help identify whether the problem lies in the retrieval or generation process.
Quick Start
Use the monitor-rag-quality skill to evaluate the quality of your RAG pipeline by providing a set of examples with questions, expected answers, and retrieved context.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferences
💻 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: monitor-rag-quality Download link: https://github.com/ContextJet-ai/awesome-llm-observability/archive/main.zip#monitor-rag-quality Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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