agent-evaluation
Evaluate agent behavior with versioned cases and explicit verifiers. Use when comparing agent or prompt changes, reproducing failures, or running agent regression tests.
newProduct ManagementAI & Automation
Agent Evaluation
Evaluate observable agent behavior against task-specific cases. Modified by AAS maintainers on 2026-09-05 to remove unsupported benchmark claims, correct uncertainty/error reporting and separate optional architecture sketches from the operating procedure.
When to Use
Use when comparing a changed agent, prompt or tool configuration, reproducing an observed failure, or estimating reliability on a declared task distribution. Do not infer product readiness from a public benchmark percentage or a generic score threshold.
Prerequisites
- A versioned case set with expected observable outcomes and permission boundaries.
- A known baseline and candidate revision, including model, prompt, tools, configuration and runtime versions.
- Authorized synthetic or redacted inputs, isolated targets and a bounded token, time and cost budget.
- A verifier that distinguishes wrong outcomes, expected safe rejections, evaluator failures and infrastructure outages. Provider access is needed only if the declared evaluation calls that provider.
Evaluation procedure
- Freeze the contract. Record case IDs and dataset revision, baseline/candidate identities, target environment, repeat plan, budgets, stopping rule and decision criteria before execution. Keep critical safety and authorization failures separate from average quality; they cannot be compensated by a highe
Subscribers only
The full skill, its 2 bundled files and every download is included with every paid Complete AI plan.
Details
| Source | vibeship-spawner-skills (Apache 2.0) |
|---|---|
| License | — |
| Risk label | safe ("critical" means the skill may run commands or touch files — read before use) |
| Files | SKILL.md, references/architecture-sketches.md |
| Added | 2026-02-27 |
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