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{"type":"item.completed","item":{"id":"item_1","type":"agent_message","text":"```python\nimport json, numpy as np\nexec(open('/work/design_v5.py').read())\nfinal_config=json.load(open('/work/config_v5.json'))\ninstall(final_config)\nfor name in NAMES:\n    value=load(name)\n    assert value.shape==tuple(SHAPES[name])\n    assert value.dtype==np.float32\n    assert np.isfinite(value).all()\nassert set(saved())==set(NAMES)\njson.dump(final_config,open('/work/final_config.json','w'),indent=2)\nprint('Final policy saved and all 14 tensors checked.')\nprint('Design: liberty-based group signals, guarded captures, atari escapes,')\nprint('self-atari avoidance, eye preservation, connection/shape preferences,')\nprint('local influence, center opening, and conservative passing.')\nprint('No training, search, or sandbox forward evaluations were used.')\n```\n"}}
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