skills/agent-evaluation/SKILL.md
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.
npx skillsauth add williamlimasilva/.copilot agent-evaluationInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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
development
Anxiety-aware, evidence-driven collaboration for stalled or high-stakes work when a user says uncertainty, repeated setbacks, or lack of visible progress is causing significant anxiety or distress. Use immediately when explicitly invoked; when this fit is only inferred from the user's own account, ask permission before applying it. Preserve the user's ideal and turn grounded perspective-taking into persistent, bounded problem solving. Do not use to diagnose, provide therapy, manufacture certainty, or lower goals for reassurance.
development
Build, review, debug, package, and test Roslyn diagnostic analyzers, code fix providers, and incremental source generators. Use for DiagnosticAnalyzer, CodeFixProvider, IIncrementalGenerator, IOperation analysis, Microsoft.CodeAnalysis dependency pinning, Roslyn test harnesses, C#/VB tests, and analyzer NuGet packaging.
testing
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development
Polish any GitHub repository's surface — labels (emoji rating tiers, P0–P3 priority, impact severity), issue forms, PR template, CI workflows, CODEOWNERS, rulesets, docs. Repo meta & config only — no code logic touched. Use when creating a new repo or polishing an existing one.