{
  "analysis": "Frame 3->4 would cost ~630 bytes with naive cursor positioning, which is way over the 57.5 byte/frame average budget. I need smarter optimization. Let me analyze overall statistics and explore better strategies like relative cursor movement.",
  "plan": "Analyze the total cost across all frames to understand what optimization level is needed. Also explore if relative cursor movements (CUF, CUD, etc.) can save bytes.",
  "commands": [
    {
      "keystrokes": "python3 -c \"\nimport struct\nwith open('/app/frames.tza', 'rb') as f:\n    f.read(4)\n    w, h = struct.unpack('<HH', f.read(4))\n    n_frames, max_bytes = struct.unpack('<II', f.read(8))\n    \n    frames = []\n    for i in range(n_frames):\n        frames.append(f.read(w*h))\n    \n    # Calculate total changes and runs\n    total_changes = 0\n    total_runs = 0\n    for i in range(1, n_frames):\n        changes = [frames[i-1][j] != frames[i][j] for j in range(w*h)]\n        for r in range(h):\n            in_run = False\n            for c in range(w):\n                idx = r * w + c\n                if changes[idx]:\n                    total_changes += 1\n                    if not in_run:\n                        in_run = True\n                        total_runs += 1\n                else:\n                    in_run = False\n    \n    print(f'Total changes across all frames: {total_changes}')\n    print(f'Total runs across all frames: {total_runs}')\n    print(f'Avg changes/frame: {total_changes/n_frames:.1f}')\n    print(f'Avg runs/frame: {total_runs/n_frames:.1f}')\n    print(f'Est cost with cursor pos: {total_runs * 7 + total_changes + n_frames}')\n    print(f'Budget: {max_bytes}')\n\"\n",
      "duration": 2.0
    }
  ]
}