AI & ML

AI-assisted test generation + curation: 3 skills (ai-spec-coverage-mapper, ai-test-generator, model-based-test-graph-author) and 3 agents (ai-test-curator, ai-test-shallow-coverage-critic, mbt-suite-builder).

Jupyter notebook testing: 4 skills (nbval-tests, notebook-ci-pipeline-author, papermill-tests, testbook-tests) and 1 agent (notebook-quality-reviewer). Covers full-notebook regression (nbval), function-level unit tests (testbook), and parameterized execution (papermill).

LLM and prompt evaluation: 7 skills (deepeval-evaluation, giskard-llm, langfuse-tracing, llm-regression-suite-author, openai-evals, promptfoo-evaluation, ragas-evaluation) and 2 agents (llm-red-team-planner, prompt-eval-reviewer). Covers the mainstream OSS LLM-eval ecosystem: Promptfoo + OpenAI Evals + DeepEval + Ragas for functional eval, Giskard for adversarial scan, Langfuse for production observability.

ML model testing: 6 skills (alibi-explainability, deepchecks-tests, evidently-monitoring, fairlearn-fairness, giskard-tests, model-performance-regression-gate) and 2 agents (data-drift-incident-responder, model-fairness-reviewer). Covers vulnerability scanning, drift monitoring, group fairness, and per-prediction explainability.

Search relevance testing: 6 skills (elasticsearch-relevance-tests, hybrid-search-eval-author, judgment-list-author, opensearch-relevance-tests, solr-relevance-tests, vector-search-recall-tests) and 1 agent (relevance-regression-reviewer). IR-metrics-driven NDCG / MRR / Recall@k regression detection.