---

name: eval description: "Use this sub-skill when designing, generating, grading, analyzing, comparing, or optimizing Agents CLI evaluation datasets and metrics for ADK agents." metadata: disco-role: operating author: Google license: Apache-2.0 version: 1.3.1 requires: bins: - agents-cli install: "uv tool install google-agents-cli" disable-model-invocation: true license: Apache 2.0

Evaluation Workflows

Use this sub-skill inside the google-agents-cli repo skill. It is a router plus operating checklist; move into the bundled references for full command flags, schemas, and examples.

When to Use

• The user wants to create datasets, run inference traces, grade, analyze, compare, or optimize agent behavior.
• The task mentions tests/eval, eval_config.yaml, metrics, LLM-as-judge, user simulation, or multimodal eval.
• You need quality checks that are more robust than brittle pytest over model text.

Workflow

1. Define the task-specific success criteria and dataset schema.
2. Generate traces, grade with suitable metrics, then analyze/compare results.
3. Use LLM-as-judge and user simulation only with explicit schemas and review.
4. Feed failures back into agent code or prompts; repeat the eval-fix loop.

Read These References

• references/eval-guide.md — read for eval guide details.
• references/builtin-tools-eval.md — read for builtin tools eval details.
• references/dataset_schema.md — read for dataset_schema details.
• references/metrics-guide.md — read for metrics guide details.
• references/multimodal-eval.md — read for multimodal eval details.
• references/user-simulation.md — read for user simulation details.

Verification and Safety

Safe checks: validate dataset/config shape and run help/parser checks; real eval generate/grade may call models and needs budget.

Boundaries

• Does not author arbitrary agent code except as a feedback target.
• Does not run cloud-side evals or judge models without credentials/budget approval.

Related Sub-Skills

• ../workflow/SKILL.md — lifecycle routing and approval gates.
• ../scaffold/SKILL.md — project creation/enhancement.
• ../adk-code/SKILL.md — ADK Python implementation patterns.
• ../eval/SKILL.md — evaluation loops and metrics.
• ../deploy/SKILL.md — deployment and infrastructure.
• ../publish/SKILL.md — Gemini Enterprise registration.
• ../observability/SKILL.md — logging, tracing, and analytics.