对 LLM 代理进行测试和基准测试,包括行为测试、能力评估、可靠性指标和生产监控,即使是顶级代理在实际基准上的成绩也低于 50% 使用场合:代理测试、代理评估、基准代理、代理可靠性、测试代理。
数据来源:ClawHub。 在 ClawSkills 查看
选择你使用的 Agent
方法一:命令行安装(推荐)
推荐(无需提前安装 clawhub)
npx clawhub@latest --dir ~/.claude/skills install agent-evaluation或使用 clawhub CLI(需提前安装)
clawhub --dir ~/.claude/skills install agent-evaluation⚠️ 需要 Node.js 18+,没有 Node?请使用下方方法二直接下载 ZIP。 安装 Node.js →
方法二:手动下载安装(无需 Node)
下载 ZIP,解压后将文件夹放到以下路径,重启 Agent 即可:
安装路径
~/.claude/skills/agent-evaluation/💡解压后将文件夹放到上方路径,重启 Agent 即可生效
--- name: agent-evaluation description: "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." source: vibeship-spawner-skills (Apache 2.0) ---
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
Run tests multiple times and analyze result distributions
Define and test agent behavioral invariants
Actively try to break agent behavior
| 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 |
Works well with: multi-agent-orchestration, agent-communication, autonomous-agents
安装 代理商评价 后,可以对 AI 说这些话来触发它
Help me get started with Agent Evaluation
Explains what Agent Evaluation does, walks through the setup, and runs a quick demo based on your current project
Use Agent Evaluation to testing and benchmarking LLM agents including behavioral testing, c...
Invokes Agent Evaluation with the right parameters and returns the result directly in the conversation
What can I do with Agent Evaluation in my developer & devops workflow?
Lists the top use cases for Agent Evaluation, with example commands for each scenario
将技能文件夹放到 ~/.claude/skills/agent-evaluation/ 目录(个人级,所有项目可用),或 .claude/skills/agent-evaluation/(项目级)。重启 AI 客户端后,用 /agent-evaluation 主动调用,或让 AI 根据上下文自动发现并使用。
代理商评价 支持 Claude、Cursor、OpenClaw,可与这些 AI 平台无缝集成,扩展其能力。
代理商评价 可免费安装使用。请查阅仓库了解许可证信息。
对 LLM 代理进行测试和基准测试,包括行为测试、能力评估、可靠性指标和生产监控,即使是顶级代理在实际基准上的成绩也低于 50% 使用场合:代理测试、代理评估、基准代理、代理可靠性、测试代理。
代理商评价 属于「Developer & DevOps」分类,该分类的技能帮助 AI 智能体在此领域执行专业任务。
Automate my developer & devops tasks using Agent Evaluation
Identifies repetitive steps in your workflow and sets up Agent Evaluation to handle them automatically