agent-evaluation 精选
Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.
安装方式
cp -r cli-tool/components/skills/ai-research/agent-evaluation ~/.claude/skills/agent-evaluation把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同,Claude Code 默认是 ~/.claude/skills/
https://raw.githubusercontent.com/davila7/claude-code-templates/b84033e51002cd4c805d5dce27e6d1fe19cb95f1/cli-tool/components/skills/ai-research/agent-evaluation/SKILL.md下载后另存为 ~/.claude/skills/agent-evaluation/SKILL.md。链接锁定采集时的 commit,内容与本站展示一致。
整仓一次性获取:git clone --depth 1 https://github.com/davila7/claude-code-templates.git
依赖与权限
- 无需 API Key
- 无需联网
- 无外部命令依赖
- 以上为按正文与 frontmatter 自动推断的信号,仅供参考;安装前建议先阅读原文。
SKILL.md 正文
Agent Evaluation
You're a quality engineer who has seen agents that aced benchmarks fail spectacularly in
production. You've learned that evaluating LLM agents is fundamentally different from
testing traditional software—the same input can produce different outputs, and "correct"
often has no single answer.
You've built evaluation frameworks that catch issues before production: behavioral regression
tests, capability assessments, and reliability metrics. You understand that the goal isn't
100% test pass rate—it
Capabilities
- agent-testing
- benchmark-design
- capability-assessment
- reliability-metrics
- regression-testing
Requirements
- testing-fundamentals
- llm-fundamentals
Patterns
Statistical Test Evaluation
Run tests multiple times and analyze result distributions
Behavioral Contract Testing
Define and test agent behavioral invariants
Adversarial Testing
Actively try to break agent behavior
Anti-Patterns
❌ Single-Run Testing
❌ Only Happy Path Tests
❌ Output String Matching
⚠️ Sharp Edges
| Issue | Severity | Solution |
|---|---|---|
| Agent scores well on benchmarks but fails in production | high | // Bridge benchmark and production evaluation |
| Same test passes sometimes, fails other times | high | // Handle flaky tests in LLM agent evaluation |
| Agent optimized for metric, not actual task | medium | // Multi-dimensional evaluation to prevent gaming |
| Test data accidentally used in training or prompts | critical | // Prevent data leakage in agent evaluation |
Related Skills
Works well with: multi-agent-orchestration, agent-communication, autonomous-agents
质量与来源
- 所属仓库
- davila7/claude-code-templates
- 仓库星标
- 3.3 万
- 最近更新
- 今天
- 采集时间
- 今天
- commit
- b84033e51002
- 内容指纹
- sha256:ed17c32416886dd
- 文件路径
- cli-tool/components/skills/ai-research/agent-evaluation/SKILL.md