{
"event": "PreToolUse",
"tool_name": "mcp__mcp-tasks__tasks_result",
"tool_input": {
"id": 359,
"response": "Successfully refactored pipeline.py from 452 LOC to 362 LOC (-90 lines, -20%).\n\nCreated 4 modular step modules:\n- step_extract.py (104 LOC) - Extraction step with file info collection\n- step_transform.py (144 LOC) - Vision, chunking, enrichment, and analysis\n- step_load.py (104 LOC) - Database persistence operations \n- step_embed.py (69 LOC) - Vector embedding generation\n\nAll modules are under 150 LOC constraint. Pipeline orchestrator is now clean and focused on workflow coordination. Each step has clear responsibilities:\n- Extract: File text extraction and metadata\n- Transform: Content transformation (vision, chunking, enrichment, analysis)\n- Load: Database persistence\n- Embed: Vector embedding generation\n\nThe refactored architecture follows separation of concerns with:\n- Clear step interface with db and progress parameters\n- Consistent error handling and cancellation checks\n- Modular design enabling easier testing and maintenance\n- Reduced complexity in main orchestrator",
"executor": "Claude Opus 4.5",
"executor_type": "anthropic_api",
"model_name": "claude-opus-4-5",
"status": "success"
}
}
{
"tool_response": [
{
"type": "text",
"text": "{\n \"success\": true,\n \"result\": {\n \"id\": 338,\n \"task_id\": 359,\n \"executor\": \"Claude Opus 4.5\",\n \"executor_type\": \"anthropic_api\",\n \"model_name\": \"claude-opus-4-5\",\n \"request\": null,\n \"response\": \"Successfully refactored pipeline.py from 452 LOC to 362 LOC (-90 lines, -20%).\\n\\nCreated 4 modular step modules:\\n- step_extract.py (104 LOC) - Extraction step with file info collection\\n- step_transform.py (144 LOC) - Vision, chunking, enrichment, and analysis\\n- step_load.py (104 LOC) - Database persistence operations \\n- step_embed.py (69 LOC) - Vector embedding generation\\n\\nAll modules are under 150 LOC constraint. Pipeline orchestrator is now clean and focused on workflow coordination. Each step has clear responsibilities:\\n- Extract: File text extraction and metadata\\n- Transform: Content transformation (vision, chunking, enrichment, analysis)\\n- Load: Database persistence\\n- Embed: Vector embedding generation\\n\\nThe refactored architecture follows separation of concerns with:\\n- Clear step interface with db and progress parameters\\n- Consistent error handling and cancellation checks\\n- Modular design enabling easier testing and maintenance\\n- Reduced complexity in main orchestrator\",\n \"status\": \"success\",\n \"error_message\": null,\n \"tokens_input\": 0,\n \"tokens_output\": 0,\n \"tokens_total\": 0,\n \"cost_usd\": 0.0,\n \"duration_ms\": 1,\n \"created_at\": \"2025-12-25T16:58:32.920383\"\n },\n \"message\": \"Result saved for Task #359\"\n}"
}
]
}