Answer AI agent evaluation questions with cited Microsoft ecosystem guidance.
npx skills add https://github.com/microsoft/eval-guide --skill eval-faq
Please help me install this Agent Skill. Skill: eval-faq Source: https://github.com/microsoft/eval-guide/tree/main/skills/eval-faq Command: npx skills add https://github.com/microsoft/eval-guide --skill eval-faq
Answers AI agent evaluation questions with practical, opinionated guidance grounded primarily in Microsoft's agent evaluation ecosystem (MS Learn, Eval Scenario Library, Triage & Improvement Playbook, Eval Guidance Kit) supplemented by select industry sources.
Ask a question using /eval-faq <your question> to receive actionable guidance.
High-intent search queries and answers about installing and using this skill.
To handle non-determinism during AI agent evaluation, you should apply practical guidance from the MS Learn four-stage framework, using scenario libraries and triage playbooks to establish baselines and iterate on variable outputs.
Evaluating tool invocation accuracy requires selecting appropriate eval methods grounded in the MS Learn framework, utilizing scenario libraries to test function calling and applying failure triage to diagnose incorrect tool-call execution.
Designing an evaluation dataset for red-teaming involves systematic expansion using the Eval Scenario Library, ensuring diverse adversarial prompts are structured to measure agent safety and robustness within the four-stage framework.
Yes, this evaluation methodology supports failure triage and root-cause analysis by synthesizing references from the Triage & Improvement Playbook to interpret results and systematically identify underlying agent errors.
You need a formal evaluation framework for AI agents when planning evals, interpreting non-deterministic results, or operationalizing systems, ensuring structured guidance from Stage 1 Define through Operationalize planning.
Relying on a single methodology for agent evaluation can limit failure detection; supplementing primary scenario libraries with red-teaming and tool-call evaluation ensures comprehensive coverage of non-deterministic behaviors.
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