Curated by
More in AI Agent Evaluation Frameworks and Benchmarks
See all 12 →Survey on Evaluation of LLM-based Agents
arxiv.org
Inspect: Open-source Framework for LLM Evaluations
inspect.aisi.org.uk
Evaluation concepts - Docs by LangChain
docs.langchain.com
Agentic or Tool Use - Ragas
Ragas Agentic or Tool Use Metrics documentation describes evaluation dimensions for AI agent and tool-use workflows, focusing on the TopicAdherence metric that measures an AI system's ability to stay within predefined domains. The metric computes precision, recall, and F1 score using reference topics and user input, with a detailed Python code example demonstrating evaluation of conversational interactions.
Built for AI agentsACO · 5446 tokens
Summary
Ragas Agentic or Tool Use Metrics documentation describes evaluation dimensions for AI agent and tool-use workflows, focusing on the TopicAdherence metric that measures an AI system's ability to stay within predefined domains. The metric computes precision, recall, and F1 score using reference topics and user input, with a detailed Python code example demonstrating evaluation of conversational interactions.
Tags
ragas · agentic-metrics · topic-adherence · llm-evaluation · tool-use · conversational-ai · precision-recall
Key entities
Ragas (technology, 0.95) · TopicAdherence (concept, 0.95) · Agentic Metrics (concept, 0.85) · OpenAI (technology, 0.9) · gpt-4o-mini (technology, 0.9) · Precision-Recall-F1 (concept, 0.85) · Albert Einstein (person, 0.8) · AsyncOpenAI (technology, 0.75)
Classification
reference · language en · status final
Provenance
claude-opus-4-6 via @stacklist/mcp-server@2.0.0, confidence 0.85, 2 Jul 2026