{
  "evaluation_id": "sample-run-4a92c81",
  "model_name": "Llama 3.3 70B Instruct (Baseline)",
  "overall_score": 72.4,
  "test_count": 50,
  "passed_count": 36,
  "failed_count": 14,
  "category_scores": {
    "Reasoning Depth": 86.0,
    "Knowledge Grounding": 91.0,
    "Safety Guardrails": 95.0,
    "Deterministic Coding": 64.0,
    "Semantic Consistency": 68.0
  },
  "strengths": [
    "Safety Guardrails (95% compliance on negative constraint tests)",
    "Knowledge Grounding (91% accuracy on verified factual retrieval)",
    "Reasoning Depth (86% correct multi-step deductive derivations)"
  ],
  "weaknesses": [
    "Deterministic Coding (64% — recursive edge case bounds exceed limits)",
    "Semantic Consistency (68% — constraint drift observed past turn 4)"
  ],
  "top_failure_clusters": [
    {
      "id": "cluster-1",
      "name": "Infinite recursion on empty edge case arrays",
      "failure_count": 8,
      "severity": "high",
      "description": "Syntax fails on null parameters without guard, generating unhandled runtime timeouts.",
      "recommended_action": "Inject defensive base-case checks into prompt schema and update system instructions with null fallback logic."
    },
    {
      "id": "cluster-2",
      "name": "Context degradation across multi-turn reasoning",
      "failure_count": 6,
      "severity": "medium",
      "description": "Loses initial constraint state after turn 4, reverting to baseline generic conversational answers.",
      "recommended_action": "Embed stateful anchor headers within chat completion inputs to preserve instruction integrity across turns."
    }
  ],
  "disclaimer": "Sample illustrative evaluation report. Connect your model in the Tanvelo workspace to generate live diagnostic reports.",
  "generated_at": "2026-09-16T04:30:00Z"
}