agent-platform-eval-flywheel
提供评估构建、指标选择与失败分析的实用流程，适合做质量回归的团队。
需访问评估数据与 SDK 权限，存在数据隐私与泄露风险。
使用 Eval Quality Flywheel 与 GenAI Evaluation SDK 对模型与代理进行系统化评估和迭代改进。
把评估模型和 agent 当成一个迭代闭环，用 Eval Quality Flywheel 和 Agent Platform GenAI Evaluation SDK 做系统化评测：建评测集、选或自定义指标、用 LLM-as-judge 打分并分析失败案例。需要比较改动前后效果、构建可复现的评估流程或找出常见失效时用。优点是流程化、可量化且便于持续改进 GenAI 系统。
▸ 展开 SKILL.md 英文原文
Measures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a fix, or when guidance is needed on Agent Platform eval methodology — including dataset schema, LLM-as-judge scoring, and common failure causes. For fine-tuning, use agent-platform-tuning. For general production deployment, use agent-platform-deploy.
帮我安装这个 skill：https://raw.githubusercontent.com/google/skills/main/skills/cloud/agent-platform-eval-flywheel/SKILL.mdcurl -fsSL "https://raw.githubusercontent.com/google/skills/main/skills/cloud/agent-platform-eval-flywheel/SKILL.md"# Agent Platform Eval Flywheel Skill
Help users evaluate and iteratively improve GenAI models and agents using the
Agent Platform GenAI Evaluation SDK (`google.genai` / `agentplatform`).
## When to use this skill
- Evaluating GenAI agents or models with the Agent Platform GenAI Evaluation
SDK (`client.evals.evaluate()`).
- Creating evaluation datasets from session traces, pandas DataFrames, or
synthetic generation.
- Selecting, configuring, or writing custom evaluation metrics.
- Analyzing rubric verdicts, loss patterns, and clustering failures.
- Suggesting concrete code/prompt improvements based on eval results.
- Evaluating a model served on an Agent Platform **endp