strands-evals

strands-evals is an LLM evaluation & observability skill for AI agents, published by strands-agents in the evals repository on GitHub. Skillspace rates strands-evals C (75/100) and it passed the safety scan; the rating is based on static analysis only.

Use when authoring evaluations with strands-agents-evals. Activates on tasks involving Case/Experiment construction, picking evaluators (Output, Trajectory, Helpfulness, Faithfulness, Coherence, Conciseness, ResponseRelevance, Harmfulness, Refusal, Stereotyping, InstructionFollowing, GoalSuccessRate, ToolSelection/ParameterAccuracy, Multimodal*), trace-based evaluation with mappers (CloudWatch, OpenSearch, OpenInference, LangChain OTel, Strands in-memory), simulators (ActorSimulator, ToolSimulator), failure detection and root-cause analysis (detect_failures, analyze_root_cause, diagnose_session), chaos / fault-injection testing (ChaosCase, ChaosExperiment, ChaosPlugin), red-team evaluation (RedTeamExperiment, AdversarialCaseGenerator, AttackSuccessEvaluator, attack strategies), or auto test-case generation (ExperimentGenerator). Trigger phrases include "evaluate this agent", "score the trajectory", "simulate a user", "diagnose the session", "generate test cases", "LLM-as-a-Judge",…

Grade

C

Quality

75 / 100

Safety

Passed

GitHub stars

162

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

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