# Agent Evals

> Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates.

- Skill: `majiayu000/agent-evals` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds add majiayu000/agent-evals`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/agent-evals/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- License: MIT
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/agent-evals

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# Agent Evals

Create repeatable checks so agent behavior improves safely over time.

## Evaluation Layers

- Unit evals: prompt-level correctness
- Tool evals: API/tool call decision quality
- End-to-end evals: realistic multi-step tasks
- Safety evals: prompt injection and data leak resistance

## CI/CD Integration

```bash
# Example eval pipeline steps
make evals-smoke
make evals-regression
make evals-safety
```

## Best Practices

- Version datasets with expected outputs.
- Track pass rates and score drift over time.
- Block deploys on critical safety regressions.

## Related Skills

- [github-actions](../../ci-cd/github-actions/) - Eval automation in CI
- [ai-agent-security](../../../security/ai/ai-agent-security/) - Security-focused eval cases