eval-agent
FeaturedRun evaluation tests against an agent to assess quality and archetype resistance
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Quality Score: 90/100
Skill Content
Details
- Author
- jmagly
- Repository
- jmagly/aiwg
- Created
- 1 years ago
- Last Updated
- today
- Language
- TypeScript
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
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Designs and runs reproducible evaluations for AI agents, prompts, tools, skills, and model-backed workflows using realistic datasets, isolated baselines, objective assertions, rubric grading, trajectory analysis, cost/latency tracking, and regression comparison. Use when measuring agent quality, optimizing skill triggering, comparing prompts or models, or gating an AI feature release. Not for ordinary deterministic unit tests.
agent-evaluate
Define behavioral contracts, run adversarial tests, and detect regressions for AI agents — invariants, edge cases, statistical analysis, and benchmark-production gap detection
agent-evaluation
Design reproducible evaluations for AI agents with representative task sets, explicit rubrics, appropriate graders, baselines, regression gates, and failure analysis. Use when defining agent quality, comparing prompts or models, validating a release, measuring tool-use reliability, investigating regressions, or deciding whether an agent is ready for production.