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{
  "id": "10383271-5fe6-4214-900a-b20961ccc58f",
  "type": "general",
  "status": "completed",
  "title": "YOLO Architecture Explorer - Kontask Card Demo",
  "description": "Interactive YOLO version comparison styled like the React example",
  "context": {
    "output": "<div style=\"background:#030712;color:#f3f4f6;padding:24px;border-radius:16px;font-family:system-ui,-apple-system,sans-serif;\"><div style=\"text-align:center;margin-bottom:24px;\"><h1 style=\"font-size:1.8rem;font-weight:bold;margin:0 0 8px 0;background:linear-gradient(to right,#60a5fa,#a78bfa,#fbbf24);-webkit-background-clip:text;-webkit-text-fill-color:transparent;background-clip:text;\">YOLO Architecture Explorer</h1><p style=\"color:#9ca3af;margin:0;\">Compare detection head designs across versions</p></div><div style=\"display:flex;justify-content:center;gap:8px;margin-bottom:24px;flex-wrap:wrap;\"><span style=\"background:#3b82f6;color:#fff;padding:8px 16px;border-radius:8px;font-weight:500;box-shadow:0 4px 6px rgba(59,130,246,0.3);transform:scale(1.05);\">YOLOv5</span><span style=\"background:#1f2937;color:#9ca3af;padding:8px 16px;border-radius:8px;\">YOLOv7</span><span style=\"background:#1f2937;color:#9ca3af;padding:8px 16px;border-radius:8px;\">YOLOv8</span><span style=\"background:#1f2937;color:#9ca3af;padding:8px 16px;border-radius:8px;\">YOLOX</span></div><div style=\"background:#111827;border-radius:16px;border:1px solid #1f2937;overflow:hidden;\"><div style=\"padding:16px;border-bottom:1px solid #1f2937;background:rgba(59,130,246,0.1);\"><div style=\"display:flex;align-items:center;justify-content:space-between;flex-wrap:wrap;gap:12px;\"><div style=\"display:flex;align-items:center;gap:12px;\"><div style=\"width:12px;height:12px;border-radius:50%;background:#3b82f6;\"></div><span style=\"font-size:1.25rem;font-weight:bold;\">YOLOv5</span><span style=\"color:#6b7280;\">(2020)</span></div><div style=\"display:flex;gap:16px;font-size:0.9rem;\"><div><span style=\"color:#6b7280;\">Approach:</span> <span style=\"background:rgba(59,130,246,0.3);color:#3b82f6;padding:2px 8px;border-radius:4px;font-weight:500;\">Anchor-based</span></div><div><span style=\"color:#6b7280;\">Head:</span> <span style=\"background:rgba(59,130,246,0.3);color:#3b82f6;padding:2px 8px;border-radius:4px;font-weight:500;\">Coupled</span></div></div></div></div><div style=\"display:flex;border-bottom:1px solid #1f2937;\"><div style=\"flex:1;padding:12px;text-align:center;border-bottom:2px solid #3b82f6;color:#3b82f6;font-weight:500;font-size:0.9rem;\">Architecture</div><div style=\"flex:1;padding:12px;text-align:center;color:#6b7280;font-size:0.9rem;\">Parameters</div><div style=\"flex:1;padding:12px;text-align:center;color:#6b7280;font-size:0.9rem;\">Strengths</div></div><div style=\"padding:24px;\"><div style=\"display:flex;gap:16px;align-items:flex-start;margin-bottom:24px;\"><div style=\"flex:1;\"><div style=\"background:#3b82f6;color:#fff;padding:6px 12px;border-radius:6px;text-align:center;font-size:0.75rem;font-weight:600;margin-bottom:8px;\">BACKBONE</div><div style=\"border:1px solid #3b82f6;color:#3b82f6;background:rgba(59,130,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;margin-bottom:4px;\">Focus</div><div style=\"border:1px solid #3b82f6;color:#3b82f6;background:rgba(59,130,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;margin-bottom:4px;\">CBS</div><div style=\"border:1px solid #3b82f6;color:#3b82f6;background:rgba(59,130,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;margin-bottom:4px;\">C3</div><div style=\"border:1px solid #3b82f6;color:#3b82f6;background:rgba(59,130,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;\">SPP</div></div><div style=\"display:flex;align-items:center;color:#4b5563;\">→</div><div style=\"flex:1;\"><div style=\"background:#3b82f6;color:#fff;padding:6px 12px;border-radius:6px;text-align:center;font-size:0.75rem;font-weight:600;margin-bottom:8px;\">NECK</div><div style=\"border:1px solid #3b82f6;color:#3b82f6;background:rgba(59,130,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;margin-bottom:4px;\">FPN</div><div style=\"border:1px solid #3b82f6;color:#3b82f6;background:rgba(59,130,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;\">PANet</div></div><div style=\"display:flex;align-items:center;color:#4b5563;\">→</div><div style=\"flex:1;\"><div style=\"background:#3b82f6;color:#fff;padding:6px 12px;border-radius:6px;text-align:center;font-size:0.75rem;font-weight:600;margin-bottom:8px;\">HEAD</div><div style=\"border:1px solid #3b82f6;color:#3b82f6;background:rgba(59,130,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;margin-bottom:4px;\">Conv layers</div><div style=\"border:1px solid #3b82f6;color:#3b82f6;background:rgba(59,130,246,0.1);padding:8px;border-radius:6px;text-align:center;font-size:0.8rem;\">Anchors (3 scales)</div></div></div><div style=\"background:rgba(31,41,55,0.5);border-radius:12px;padding:16px;\"><h3 style=\"color:#3b82f6;font-weight:600;margin:0 0 8px 0;font-size:0.95rem;\">Detection Head Details</h3><p style=\"color:#9ca3af;font-size:0.9rem;line-height:1.6;margin:0;\">YOLOv5 uses a coupled head with anchor boxes at 3 scales. Each grid cell predicts B bounding boxes, with each box predicting (x, y, w, h, objectness, class_scores). Anchors are computed via k-means clustering on the dataset.</p></div></div></div><div style=\"display:grid;grid-template-columns:1fr 1fr;gap:16px;margin-top:24px;\"><div style=\"background:#111827;border-radius:12px;padding:16px;border:1px solid #1f2937;\"><h3 style=\"color:#9ca3af;font-size:0.9rem;font-weight:600;margin:0 0 8px 0;\">Anchor-based</h3><p style=\"color:#6b7280;font-size:0.8rem;margin:0;line-height:1.5;\">Predefined box shapes guide predictions. More stable training, but requires anchor tuning per dataset.</p></div><div style=\"background:#111827;border-radius:12px;padding:16px;border:1px solid #1f2937;\"><h3 style=\"color:#9ca3af;font-size:0.9rem;font-weight:600;margin:0 0 8px 0;\">Anchor-free</h3><p style=\"color:#6b7280;font-size:0.8rem;margin:0;line-height:1.5;\">Direct regression of box coordinates. Simpler design, no anchor hyperparameters, better generalization.</p></div></div><div style=\"background:#1f2937;padding:16px;border-radius:8px;margin-top:24px;\"><h4 style=\"margin:0 0 12px 0;color:#fff;font-size:0.95rem;\">Why Opus vs Haiku Output Differs</h4><table style=\"width:100%;border-collapse:collapse;font-size:0.85rem;\"><tr style=\"border-bottom:1px solid #374151;\"><th style=\"text-align:left;padding:8px;color:#9ca3af;\">Aspect</th><th style=\"text-align:left;padding:8px;color:#9ca3af;\">Opus</th><th style=\"text-align:left;padding:8px;color:#9ca3af;\">Haiku</th></tr><tr style=\"border-bottom:1px solid #374151;\"><td style=\"padding:8px;color:#e5c07b;\">Instruction following</td><td style=\"padding:8px;color:#22c55e;\">Follows CLAUDE.md templates precisely</td><td style=\"padding:8px;color:#f97316;\">May simplify or skip complex formatting</td></tr><tr style=\"border-bottom:1px solid #374151;\"><td style=\"padding:8px;color:#e5c07b;\">HTML complexity</td><td style=\"padding:8px;color:#22c55e;\">Generates rich inline CSS</td><td style=\"padding:8px;color:#f97316;\">Often produces minimal HTML</td></tr><tr><td style=\"padding:8px;color:#e5c07b;\">Context capacity</td><td style=\"padding:8px;color:#22c55e;\">Retains full template examples</td><td style=\"padding:8px;color:#f97316;\">May lose template details</td></tr></table><p style=\"color:#9ca3af;margin:16px 0 0 0;font-size:0.85rem;line-height:1.6;\"><strong style=\"color:#fff;\">Key insight:</strong> The MCP tool is just a transport mechanism. It stores whatever HTML string Claude puts in <code style=\"background:#374151;padding:2px 6px;border-radius:3px;\">context.output</code>. The model quality determines the output quality.</p></div></div>",
    "requestedAt": "2026-01-07T02:30:00.000Z",
    "requestId": "66a311f9-a31f-46df-b79f-e5937a4d16f0",
    "choices": [
      {
        "label": "View YOLOv8",
        "value": "Show me the YOLOv8 architecture tab in the same style",
        "primary": true
      },
      {
        "label": "Compare all",
        "value": "Create a side-by-side comparison of all 4 YOLO versions"
      },
      {
        "label": "Improve Haiku",
        "value": "How can we improve Haiku's kontask output quality?"
      }
    ],
    "turnTiming": {
      "totalMs": 81543,
      "ttfeMs": 54,
      "thinkingMs": 81489,
      "toolExecutionMs": 0,
      "toolCallCount": 0,
      "thinkingPct": 100,
      "toolsPct": 0,
      "ttfePct": 0
    }
  },
  "createdBy": "claude",
  "createdAt": "2026-01-06T22:44:21.304Z",
  "updatedAt": "2026-01-06T22:44:29.735Z",
  "requestId": "66a311f9-a31f-46df-b79f-e5937a4d16f0",
  "scope": "vibetools",
  "tags": [
    "demo",
    "yolo",
    "architecture"
  ],
  "targetUser": "claude"
}