agent-skills/evals/cases/performance-optimization.json

{
  "skill_name": "performance-optimization",
  "trigger": {
    "positive": [
      {
        "prompt": "Optimize this N+1 query",
        "top_k": 1
      },
      {
        "prompt": "The dashboard takes eight seconds to load, profile it and fix the bottleneck",
        "top_k": 3
      },
      {
        "prompt": "Profile these slow database queries and add the right indexes",
        "top_k": 1
      },
      {
        "prompt": "The orders endpoint has a slow N+1 query pattern, profile it and fix the bottleneck",
        "top_k": 3
      },
      {
        "prompt": "Core Web Vitals are failing, improve our LCP",
        "top_k": 3
      }
    ],
    "negative": [
      {
        "prompt": "Draft the deprecation notice for the v1 API",
        "owner": "deprecation-and-migration"
      },
      {
        "prompt": "Design the public interface for the billing module",
        "owner": "api-and-interface-design"
      }
    ]
  },
  "evals": [
    {
      "id": 1,
      "prompt": "The products page renders slowly with 1000 items. Improve its performance.",
      "expected_output": "A measured baseline, an identified bottleneck, a targeted fix, a verified improvement, and a regression guard",
      "files": [
        "performance-optimization"
      ],
      "expectations": [
        "Performance is measured before any optimization is applied",
        "The fix targets the measured bottleneck rather than guessing",
        "Improvement is verified against the baseline after the change",
        "A concrete guard is added after verification using a synthetic performance budget or field monitoring tied to the measured user-facing metric"
      ]
    }
  ]
}