Protokoll #13151

ID13151
Zeitstempel2025-12-24 20:17:41.828303
Clientroot
IP145.224.72.140
Modellclaude-sonnet-4-20250514
Statuscompleted
Tokens709 (Input: 302, Output: 407)
Dauer78 ms
Request-Zeit2025-12-24 20:17:41.828303
Response-Zeit2025-12-24 20:17:41.906046

Request

{
    "event": "PreToolUse",
    "tool_name": "mcp__mcp-tasks__tasks_result",
    "tool_input": {
        "id": 303,
        "response": "ScoringService implementiert mit Weighted Scoring (Recency + Authority):\n\n1. **ScoringService.php erstellt**:\n   - `calculateScore(vectorScore, documentDate, authorityScore)` → Gewichteter Score\n   - `calculateRecency(date)` → 1.0 für heute, linear abnehmend zu 0.0 bei 365 Tagen\n   - `getWeights()` → Transparente Konfiguration (0.7 similarity, 0.1 recency, 0.2 authority)\n\n2. **ChatService.php integriert**:\n   - Constructor erweitert mit `ScoringService $scoring` (DI)\n   - `searchMultipleCollections()` wendet weighted_score an\n   - Sortierung nach weighted_score statt nur vector score\n\n3. **AIConfig.php aktualisiert**:\n   - `createChatService()` inkludiert ScoringService\n\n4. **DB-Schema erweitert**:\n   - `documents.authority_score FLOAT DEFAULT 0.5` hinzugefügt\n\n5. **Validierung**:\n   - PHPStan Level 7: No errors\n   - DI Check: All 39 UseCases resolvable (50 Services)\n   - Chat-Endpoint: Funktioniert\n\nScoring-Formel:\n```\nweighted_score = (0.7 × vector_similarity) + (0.1 × recency) + (0.2 × authority)\n```",
        "executor": "claude-opus-4",
        "executor_type": "claude"
    }
}

Response

{
    "tool_response": [
        {
            "type": "text",
            "text": "{\n  \"success\": true,\n  \"result\": {\n    \"id\": 270,\n    \"task_id\": 303,\n    \"executor\": \"claude-opus-4\",\n    \"executor_type\": \"claude\",\n    \"model_name\": null,\n    \"request\": null,\n    \"response\": \"ScoringService implementiert mit Weighted Scoring (Recency + Authority):\\n\\n1. **ScoringService.php erstellt**:\\n   - `calculateScore(vectorScore, documentDate, authorityScore)` → Gewichteter Score\\n   - `calculateRecency(date)` → 1.0 für heute, linear abnehmend zu 0.0 bei 365 Tagen\\n   - `getWeights()` → Transparente Konfiguration (0.7 similarity, 0.1 recency, 0.2 authority)\\n\\n2. **ChatService.php integriert**:\\n   - Constructor erweitert mit `ScoringService $scoring` (DI)\\n   - `searchMultipleCollections()` wendet weighted_score an\\n   - Sortierung nach weighted_score statt nur vector score\\n\\n3. **AIConfig.php aktualisiert**:\\n   - `createChatService()` inkludiert ScoringService\\n\\n4. **DB-Schema erweitert**:\\n   - `documents.authority_score FLOAT DEFAULT 0.5` hinzugefügt\\n\\n5. **Validierung**:\\n   - PHPStan Level 7: No errors\\n   - DI Check: All 39 UseCases resolvable (50 Services)\\n   - Chat-Endpoint: Funktioniert\\n\\nScoring-Formel:\\n```\\nweighted_score = (0.7 × vector_similarity) + (0.1 × recency) + (0....\",\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\": 0,\n    \"created_at\": \"2025-12-24T20:17:41.844695\"\n  },\n  \"message\": \"Result saved for Task #303\"\n}"
        }
    ]
}
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