skills/agentscope/_scores.json

{
  "version": "1.0.0",
  "skillHash": "sha256:517f3f63f4d55ace9f51e20e02bae10386a9fef60d558ed6af4f6420d6f99ba3",
  "scoredAt": "2026-05-13T12:20:59.343Z",
  "backend": "ollama",
  "model": "gpt-oss:20b",
  "quality": {
    "score": 77,
    "dimensions": {
      "clarity": "PASS",
      "completeness": "WEAK",
      "conciseness": "PASS",
      "actionability": "PASS",
      "crossPlatform": "FAIL",
      "examples": "PASS"
    },
    "issues": [
      {
        "severity": "MEDIUM",
        "category": "completeness",
        "detail": "The instructions do not cover error handling or edge cases, focusing only on happy paths."
      },
      {
        "severity": "HIGH",
        "category": "crossPlatform",
        "detail": "The skill is tightly coupled to the AgentScope framework, limiting its applicability to other AI agent frameworks."
      }
    ]
  },
  "security": {
    "verdict": "SAFE",
    "issues": []
  },
  "impact": {
    "multiplier": 10,
    "baselineAvg": 0,
    "treatmentAvg": 100,
    "scenarios": [
      {
        "name": "multi-agent-dashboard",
        "baseline": 0,
        "treatment": 100,
        "rationale": "Response A fully satisfies all rubric requirements, while Response B does not implement any of the required components."
      },
      {
        "name": "audit-trail-claim-processing",
        "baseline": 0,
        "treatment": 100,
        "rationale": "Response A fully satisfies all rubric requirements, while Response B does not implement an AuditTrail or export the audit to a PDF as specified."
      },
      {
        "name": "decision-logging-debug",
        "baseline": 0,
        "treatment": 100,
        "rationale": "Response A fully satisfies the rubric, while Response B does not use the required DecisionLogger or iterate over its decisions."
      }
    ]
  }
}