Generates tailored giskard.checks evaluation suites for RAG (Retrieval-Augmented Generation) systems. Use whenever a user describes a Q&A bot grounded in documents, a knowledge-base chatbot, a retrieval system, or wants to evaluate answer groundedness, faithfulness, hallucination, retrieval quality, citation accuracy, or out-of-scope handling. Triggers on phrases like "evaluate my RAG", "test my retrieval", "check groundedness", "build a RAG eval suite", "eval my chatbot answers from docs", "test if my agent hallucinates", "check if my answers are faithful to the sources", or any evaluation task involving an agent that answers from documents, FAQs, wikis, or a knowledge base. Use this skill even when the user does not explicitly say "RAG" but describes an agent grounded in documents. For adversarial / red-teaming evaluation, use the scenario-generator skill instead. This skill focuses on quality, not safety.
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategorySecurityStars0
About this skill
Generates tailored giskard.checks evaluation suites for RAG (Retrieval-Augmented Generation) systems. Use whenever a user describes a Q&A bot grounded in documents, a knowledge-base chatbot, a retrieval system, or wants to evaluate answer groundedness, faithfulness, hallucination, retrieval quality, citation accuracy, or out-of-scope handling. Triggers on phrases like "evaluate my RAG", "test my retrieval", "check groundedness", "build a RAG eval suite", "eval my chatbot answers from docs", "test if my agent hallucinates", "check if my answers are faithful to the sources", or any evaluation task involving an agent that answers from documents, FAQs, wikis, or a knowledge base. Use this skill even when the user does not explicitly say "RAG" but describes an agent grounded in documents. For adversarial / red-teaming evaluation, use the scenario-generator skill instead. This skill focuses on quality, not safety.
Quick start
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Generates tailored giskard.checks evaluation suites for RAG (Retrieval-Augmented Generation) systems. Use whenever a user describes a Q&A bot grounded in documents, a knowledge-base chatbot, a retrieval system, or wants to evaluate answer groundedness, faithfulness, hallucination, retrieval quality, citation accuracy, or out-of-scope handling. Triggers on phrases like "evaluate my RAG", "test my retrieval", "check groundedness", "build a RAG eval suite", "eval my chatbot answers from docs", "test if my agent hallucinates", "check if my answers are faithful to the sources", or any evaluation task involving an agent that answers from documents, FAQs, wikis, or a knowledge base. Use this skill even when the user does not explicitly say "RAG" but describes an agent grounded in documents. For adversarial / red-teaming evaluation, use the `scenario-generator` skill instead. This skill focuses on quality, not safety.
About this listing
Category
Security
Reported license
Apache-2.0
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLI