{
  "analysis": "Still way over budget. The cursor tracking is inefficient. I need a completely different approach. Let me analyze the actual cost structure more carefully and design a simpler, more efficient encoding.",
  "plan": "Try a simpler approach: use absolute positioning (ESC[r;cH) for each changed row, and decide between EL+rewrite vs partial updates based on change density. Process rows in order to minimize positioning overhead.",
  "commands": [
    {
      "keystrokes": "python3 -c \"\nimport struct\n\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    frames = [f.read(w*h) for _ in range(n_frames)]\n\n# Analyze per-row change density across all frames\nrow_change_counts = [0] * h\nfor i in range(1, n_frames):\n    for r in range(h):\n        if frames[i-1][r*w:(r+1)*w] != frames[i][r*w:(r+1)*w]:\n            row_change_counts[r] += 1\n\nprint(f'Rows most often changed:')\nfor r in sorted(range(h), key=lambda x: -row_change_counts[x])[:10]:\n    print(f'  Row {r}: {row_change_counts[r]} times')\n\n# Calculate optimal strategy cost\n# Strategy: For each changed row, use ESC[r;1H then either:\n#   - ESC[2K + rewrite (4 + w bytes)\n#   - or partial updates with runs\n\ndef pos_cost(r, c):\n    return 3 + len(str(r)) + 1 + len(str(c))  # ESC[r;cH\n\ntotal_cost = 0\n\n# First frame: write all non-space using runs\nframe0 = frames[0]\nfor r in range(h):\n    row = frame0[r*w:(r+1)*w]\n    # Find runs of non-space\n    in_run = False\n    run_start = 0\n    for c in range(w):\n        if row[c] != 32:\n            if not in_run:\n                in_run = True\n                run_start = c\n        else:\n            if in_run:\n                in_run = False\n                run_len = c - run_start\n                total_cost += pos_cost(r+1, run_start+1) + run_len\n    if in_run:\n        run_len = w - run_start\n        total_cost += pos_cost(r+1, run_start+1) + run_len\ntotal_cost += 1  # delimiter\n\nprint(f'Frame 0 cost: {total_cost}')\n\n# Subsequent frames\nfor i in range(1, n_frames):\n    frame_cost = 0\n    for r in range(h):\n        prev_row = frames[i-1][r*w:(r+1)*w]\n        curr_row = frames[i][r*w:(r+1)*w]\n        if prev_row == curr_row:\n            continue\n        \n        # Count changes and find runs\n        changes = [c for c in range(w) if prev_row[c] != curr_row[c]]\n        if not changes:\n            continue\n        \n        # Find runs\n        runs = []\n        run_start = changes[0]\n        run_end = changes[0]\n        for c in changes[1:]:\n            if c == run_end + 1:\n                run_end = c\n            else:\n                runs.append((run_start, run_end))\n                run_start = run_end = c\n        runs.append((run_start, run_end))\n        \n        # Cost: position + run content for each run\n        for start, end in runs:\n            frame_cost += pos_cost(r+1, start+1) + (end - start + 1)\n    \n    total_cost += frame_cost + 1\n\nprint(f'Total cost: {total_cost}')\nprint(f'Budget: {max_bytes}')\nprint(f'Over/under: {total_cost - max_bytes}')\n\"\n",
      "duration": 3.0
    }
  ]
}