AI Agent Evaluation Metrics: What It Says vs What It Does?

AI agent evaluation metrics explained: 9 metrics for what your agent says, and the checks that prove what it actually did. 📢 Agent Assurance by TestMu AI is testing that grades what an AI agent actually changed, not what it says it did. 📢 Agent Testing by TestMu AI checks how a chat, voice, phone, video or image agent behaves before and after release. What you'll learn: • Why exact-match tests break for AI agents, and how a score + threshold replaces them • Set 1, what the agent says: hallucination, bias, completeness, response quality, context awareness, conversation flow, user satisfaction, file handling, file generation • Set 2, what the agent does: tool use, effect verification, safety under prompt injection, reliability • Why "unable to verify" should never count as a pass • Which one you need: Agent Testing, Agent Assurance, or both Get started with Rook CLI npm install -g @testmuai/rook@latest rook --help Agent Assurance: https://www.testmuai.com/agent-assurance/ Rook CLI: https://www.testmuai.com/rook-cli/ Agent Testing: https://www.testmuai.com/agent-testing/ IVR testing: https://www.testmuai.com/ivr-testing/ Chapters 00:00 Your agent said "done" but nothing happened 00:28 Why exact-match tests break for AI agents 00:58 How agent evals work: score + threshold 01:25 Set 1: What the agent says 01:52 Hallucination detection (Air Canada case) 02:41 Bias detection 03:38 Completeness 04:02 Response quality 04:39 Context awareness 05:01 Conversation flow 05:35 User satisfaction 05:59 File handling and file generation 06:23 Set 2: What the agent does 07:03 Tool use: calls vs allowed tools 07:18 Effect verification: did it actually happen? 07:37 Safety: prompt injection attacks 07:53 Reliability: "unable to verify" isn't a pass 08:21 Reading agent test results 08:45 Agent Assurance and Rook CLI 09:38 Agent Testing vs Agent Assurance 10:05 Before your next release #AIAgents #AgentEvaluation #LLMEvaluation #AIAgentTesting #TestMuAI