Agent Evaluation
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.
Best use case
Agent Evaluation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using Agent Evaluation should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/agent-evaluation-majiayu000/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Agent Evaluation Compares
| Feature / Agent | Agent Evaluation | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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`
Related Skills
advanced-evaluation
Master LLM-as-a-Judge evaluation techniques including direct scoring, pairwise comparison, rubric generation, and bias mitigation. Use when building evaluation systems, comparing model outputs, or establishing quality standards for AI-generated content.
llm-evaluation
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.
evaluation
Imported skill evaluation from anthropic
anthropic-evaluations
This skill should be used when the user asks to "create evals", "evaluate an agent", "build evaluation suite", or mentions agent testing, graders, or benchmarks. Also suggest when building coding agents, conversational agents, or research agents that need quality assurance.
bgo
Automates the complete Blender build-go workflow, from building and packaging your extension/add-on to removing old versions, installing, enabling, and launching Blender for quick testing and iteration.
mcp-create-declarative-agent
Skill converted from mcp-create-declarative-agent.prompt.md
MCP Architecture Expert
Design and implement Model Context Protocol servers for standardized AI-to-data integration with resources, tools, prompts, and security best practices
mathem-shopping
Automatiserar att logga in på Mathem.se, söka och lägga till varor från en lista eller recept, hantera ersättningar enligt policy och reservera leveranstid, men lämnar varukorgen redo för manuell checkout.
math-modeling
本技能应在用户要求"数学建模"、"建模比赛"、"数模论文"、"数学建模竞赛"、"建模分析"、"建模求解"或提及数学建模相关任务时使用。适用于全国大学生数学建模竞赛(CUMCM)、美国大学生数学建模竞赛(MCM/ICM)等各类数学建模比赛。
matchms
Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.
managing-traefik
Manages Traefik reverse proxy for local development. Use when routing domains to local services, configuring CORS, checking service health, or debugging connectivity issues.
managing-skills
Install, find, update, and manage agent skills. Use when the user wants to add a new skill, search for skills that do something, check if skills are up to date, or update existing skills. Triggers on: install skill, add skill, get skill, find skill, search skill, update skill, check skills, list skills.