Protokoll #30153

ID30153
Zeitstempel2025-12-30 04:32:24.872354
Clientroot
IP145.224.72.245
Modellclaude-sonnet-4-20250514
Statuscompleted
Tokens579 (Input: 23, Output: 556)
Dauer84 ms
Request-Zeit2025-12-30 04:32:24.872354
Response-Zeit2025-12-30 04:32:24.956512

Request

{
    "event": "PreToolUse",
    "tool_name": "mcp__mcp-tasks__tasks_get",
    "tool_input": {
        "id": 501
    }
}

Response

{
    "tool_response": [
        {
            "type": "text",
            "text": "{\n  \"success\": true,\n  \"task\": {\n    \"id\": 501,\n    \"uuid\": \"aa5602a7-5be7-4236-8f14-8314e83e3e93\",\n    \"title\": \"Nacharbeit: Knowledge-Semantik für 388 bestehende Entities\",\n    \"description\": \"## Ziel\\nBatch-Analyse aller bestehenden Entities mit Wissens-Semantik (semantic_role, functional_category, context_meaning).\\n\\n## Code-Wahrheit (Ist-Zustand)\\n\\n### Datenbank-Status\\n```sql\\nSELECT COUNT(*) FROM entities;  -- 444\\nSELECT COUNT(*) FROM entity_knowledge_semantics;  -- 56\\n-- Lücke: 388 Entities (87.4%) ohne Analyse\\n```\\n\\n### KnowledgeSemanticAnalyzeStep (step_semantic_extended.py:237-326)\\n```python\\nclass KnowledgeSemanticAnalyzeStep:\\n    PROMPT_TEMPLATE = \\\"\\\"\\\"Analysiere die Bedeutung dieser Entität im Kontext...\\\"\\\"\\\"\\n    \\n    def execute(self, entities: list, config: dict) -> list:\\n        # Benötigt: entity.name, entity.type, entity.context (aus Chunk)\\n```\\n\\n## Technische Herausforderungen\\n1. **Kontext-Beschaffung:** Entity → chunk_entities → chunks.content\\n2. **Rate-Limiting:** 388 Entities × ~3s\/Entity = ~20 Minuten\\n3. **JSON-Properties:** Strukturierte Eigenschaften speichern\\n\\n## Umsetzung\\n1. Neues Script: `backfill_knowledge_semantics.py`\\n2. Query mit JOIN:\\n```sql\\nSELECT e.id, e.name, e.type, c.content as context\\nFROM entities e\\nJOIN chunk_entities ce ON e.id = ce.entity_id\\nJOIN chunks c ON ce.chunk_id = c.id\\nLEFT JOIN entity_knowledge_semantics eks ON e.id = eks.entity_id\\nWHERE eks.id IS NULL\\nGROUP BY e.id\\n```\\n3. Batch-Verarbeitung mit Kontext-Aggregation\\n\\n## Akzeptanzkriterien\\n- [ ] Script erstellt und getestet\\n- [ ] Alle 388 Entities analysiert\\n- [ ] Properties als valides JSON gespeichert\\n- [ ] Logging in pipeline_log\",\n    \"type\": \"ai_task\",\n    \"status\": \"in_progress\",\n    \"created_by\": \"mcp-tasks\",\n    \"created_by_type\": \"ai\",\n    \"parent_task_id\": null,\n    \"due_date\": null,\n    \"created_at\": \"2025-12-28T02:37:30.166447\",\n    \"updated_at\": \"2025-12-28T02:49:42.112332\",\n    \"completed_at\": null,\n    \"metadata\": {}\n  },\n  \"assignments\": [],\n  \"results\": []\n}"
        }
    ]
}
← Vorheriger Zur Liste Nächster →