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Cursor Response JSON-Struktur - Spezifikation

Stand: Februar 2026 Zweck: Definition der JSON-Antwortstruktur fuer die Chat-API-Komponente, in der Antwortteile als einzelne Dokumente erfasst werden

1. Design-Prinzip

Eine LLM-Antwort besteht typischerweise aus verschiedenen Segmenten: erklaerenden Texten, Code-Referenzen, neuen Code-Bloecken, Tool-Aufrufen, Datei-Aenderungen und Plaenen. Diese Segmente werden als einzelne Dokumente in einem Array erfasst, um sie einzeln verarbeiten, rendern und referenzieren zu koennen.

2. Top-Level Response

{
  "id": "chat_<uuid>",
  "conversationId": "conv_<uuid>",
  "model": "claude-4.6-opus",
  "mode": "agent | plan | ask | debug",
  "created": "2026-02-23T10:30:00Z",
  "status": "completed | streaming | error",
  "documents": [ /* Array von Document-Objekten */ ],
  "usage": {
    "promptTokens": 2450,
    "completionTokens": 890,
    "totalTokens": 3340
  },
  "metadata": {
    "duration_ms": 4520,
    "toolCallCount": 3,
    "turnCount": 2
  }
}

Feld-Beschreibung

Feld Typ Beschreibung
id string Eindeutige ID dieser Antwort
conversationId string ID der laufenden Konversation (fuer Multi-Turn)
model string Verwendetes LLM-Modell
mode enum Aktiver Modus: agent, plan, ask, debug
created ISO 8601 Zeitstempel der Erstellung
status enum Status: completed, streaming, error
documents array Geordnetes Array der Antwort-Dokumente
usage object Token-Verbrauch
metadata object Zusaetzliche Metadaten

3. Document Types

Jedes Dokument im documents[] Array hat folgende Basis-Struktur:

{
  "id": "doc_<sequenzNummer>",
  "type": "<documentType>",
  "sequence": 1,
  "content": "...",
  "metadata": { /* typ-spezifische Metadaten */ }
}

3.1 text - Erklaerungstext

Freitext-Erklaerungen, Beschreibungen, Instruktionen des AI-Assistenten.

{
  "id": "doc_001",
  "type": "text",
  "sequence": 1,
  "content": "Ich werde eine Authentication-Middleware implementieren, die JWT-Token validiert und den Request-Context mit User-Informationen anreichert.\n\nDafuer sind folgende Schritte noetig:",
  "metadata": {
    "format": "markdown"
  }
}

3.2 code_reference - Verweis auf existierenden Code

Referenz auf bestehenden Code im Projekt (Cursor's startLine:endLine:filepath Format).

{
  "id": "doc_002",
  "type": "code_reference",
  "sequence": 2,
  "content": "def main():\n    app = Flask(__name__)\n    app.register_blueprint(api_bp)",
  "metadata": {
    "filePath": "src/main.py",
    "startLine": 12,
    "endLine": 14,
    "language": "python"
  }
}

3.3 code_block - Neuer/vorgeschlagener Code

Code-Block fuer neuen oder vorgeschlagenen Code, der nicht direkt einer Datei zugeordnet ist.

{
  "id": "doc_003",
  "type": "code_block",
  "sequence": 3,
  "content": "from functools import wraps\nfrom flask import request, jsonify\nimport jwt\n\ndef authMiddleware(f):\n    @wraps(f)\n    def decorated(*args, **kwargs):\n        token = request.headers.get('Authorization')\n        if not token:\n            return jsonify({'error': 'Token fehlt'}), 401\n        try:\n            data = jwt.decode(token, SECRET_KEY, algorithms=['HS256'])\n            request.userId = data['userId']\n        except jwt.InvalidTokenError:\n            return jsonify({'error': 'Ungueltiger Token'}), 401\n        return f(*args, **kwargs)\n    return decorated",
  "metadata": {
    "language": "python",
    "purpose": "new_code"
  }
}

3.4 file_edit - Datei-Aenderung

Konkrete Aenderung an einer bestehenden oder neuen Datei.

{
  "id": "doc_004",
  "type": "file_edit",
  "sequence": 4,
  "content": "from functools import wraps\nfrom flask import request, jsonify\nimport jwt\n\nSECRET_KEY = 'your-secret-key'\n\ndef authMiddleware(f):\n    ...",
  "metadata": {
    "filePath": "src/middleware/auth.py",
    "operation": "create",
    "language": "python",
    "diff": null
  }
}

Operationen:

Operation Beschreibung
create Neue Datei erstellen
edit Bestehende Datei aendern
delete Datei loeschen
rename Datei umbenennen

Bei edit wird zusaetzlich ein Diff mitgeliefert:

{
  "id": "doc_005",
  "type": "file_edit",
  "sequence": 5,
  "content": "app.register_blueprint(api_bp)\napp.register_blueprint(auth_bp)",
  "metadata": {
    "filePath": "src/main.py",
    "operation": "edit",
    "language": "python",
    "diff": {
      "oldString": "app.register_blueprint(api_bp)",
      "newString": "app.register_blueprint(api_bp)\napp.register_blueprint(auth_bp)",
      "startLine": 14,
      "endLine": 14
    }
  }
}

3.5 tool_call - Tool-Aufruf und Ergebnis

Dokumentiert einen Tool-Aufruf inklusive Argumente und Ergebnis.

{
  "id": "doc_006",
  "type": "tool_call",
  "sequence": 6,
  "content": null,
  "metadata": {
    "toolName": "codebase_search",
    "toolCallId": "call_abc123",
    "arguments": {
      "query": "Where is the Flask app initialized?",
      "target_directories": ["src/"],
      "explanation": "Find the main app entry point"
    },
    "result": {
      "status": "success",
      "data": "Found in src/main.py:12 - app = Flask(__name__)"
    },
    "duration_ms": 320
  }
}

3.6 terminal_command - Terminal-Ausfuehrung

Dokumentiert die Ausfuehrung eines Terminal-Kommandos.

{
  "id": "doc_007",
  "type": "terminal_command",
  "sequence": 7,
  "content": null,
  "metadata": {
    "command": "pip install PyJWT flask",
    "workingDirectory": "/path/to/project",
    "exitCode": 0,
    "output": "Successfully installed PyJWT-2.8.0 flask-3.0.0",
    "duration_ms": 5200,
    "permissions": ["network"]
  }
}

3.7 plan - Strukturierter Plan

Ergebnis des Plan-Modus oder eines create_plan Tool-Aufrufs.

{
  "id": "doc_008",
  "type": "plan",
  "sequence": 8,
  "content": "# Authentication Middleware\n\n## Uebersicht\nImplementierung einer JWT-basierten Auth-Middleware...\n\n## Dateien\n- `src/middleware/auth.py` (neu)\n- `src/main.py` (aendern)\n- `requirements.txt` (aendern)",
  "metadata": {
    "title": "Auth Middleware Implementation",
    "overview": "JWT-basierte Authentication-Middleware mit Token-Validierung",
    "todos": [
      {
        "id": "create-middleware",
        "content": "Auth-Middleware-Modul erstellen",
        "status": "pending",
        "dependencies": []
      },
      {
        "id": "register-blueprint",
        "content": "Blueprint in main.py registrieren",
        "status": "pending",
        "dependencies": ["create-middleware"]
      },
      {
        "id": "update-deps",
        "content": "PyJWT zu requirements.txt hinzufuegen",
        "status": "pending",
        "dependencies": []
      },
      {
        "id": "protect-routes",
        "content": "Schuetzenswerte Routes mit Decorator versehen",
        "status": "pending",
        "dependencies": ["create-middleware", "register-blueprint"]
      }
    ],
    "format": "markdown"
  }
}

3.8 clarification - Klaerende Frage

Klaerende Rueckfrage des AI-Assistenten an den User (haeufig im Plan Mode).

{
  "id": "doc_009",
  "type": "clarification",
  "sequence": 9,
  "content": "Bevor ich den Plan finalisiere, habe ich folgende Fragen:",
  "metadata": {
    "questions": [
      {
        "id": "q1",
        "text": "Soll die Middleware JWT oder Session-basierte Auth verwenden?",
        "options": [
          { "id": "jwt", "label": "JWT Token-basiert" },
          { "id": "session", "label": "Session-basiert mit Cookies" }
        ]
      },
      {
        "id": "q2",
        "text": "Welche Routes sollen geschuetzt werden?",
        "options": [
          { "id": "all", "label": "Alle ausser Login/Register" },
          { "id": "selective", "label": "Nur explizit markierte Routes" }
        ]
      }
    ]
  }
}

3.9 error - Fehlermeldung

Fehlermeldung bei Tool-Ausfuehrung oder LLM-Fehler.

{
  "id": "doc_010",
  "type": "error",
  "sequence": 10,
  "content": "Die Datei konnte nicht gelesen werden",
  "metadata": {
    "errorCode": "FILE_NOT_FOUND",
    "source": "read_file",
    "details": "src/middleware/auth.py does not exist"
  }
}

3.10 todo_update - Task-Status-Aenderung

Aenderung am Task-Tracking waehrend der Ausfuehrung.

{
  "id": "doc_011",
  "type": "todo_update",
  "sequence": 11,
  "content": null,
  "metadata": {
    "todos": [
      { "id": "create-middleware", "status": "completed" },
      { "id": "register-blueprint", "status": "in_progress" }
    ]
  }
}

4. Vollstaendiges Response-Beispiel

Ein realistisches Beispiel fuer die Anfrage "Implementiere JWT Authentication":

{
  "id": "chat_7f3a2b1c",
  "conversationId": "conv_9e8d7c6b",
  "model": "claude-4.6-opus",
  "mode": "agent",
  "created": "2026-02-23T10:30:00Z",
  "status": "completed",
  "documents": [
    {
      "id": "doc_001",
      "type": "text",
      "sequence": 1,
      "content": "Ich analysiere zuerst die bestehende Projektstruktur, um die beste Integrationsstrategie zu finden.",
      "metadata": { "format": "markdown" }
    },
    {
      "id": "doc_002",
      "type": "tool_call",
      "sequence": 2,
      "content": null,
      "metadata": {
        "toolName": "codebase_search",
        "toolCallId": "call_001",
        "arguments": {
          "query": "Where is the Flask app initialized?",
          "target_directories": ["src/"]
        },
        "result": { "status": "success", "data": "src/main.py:12" },
        "duration_ms": 280
      }
    },
    {
      "id": "doc_003",
      "type": "tool_call",
      "sequence": 3,
      "content": null,
      "metadata": {
        "toolName": "read_file",
        "toolCallId": "call_002",
        "arguments": { "target_file": "src/main.py" },
        "result": {
          "status": "success",
          "data": "import os\nfrom flask import Flask\n\ndef main():\n    app = Flask(__name__)\n    app.register_blueprint(api_bp)\n    return app"
        },
        "duration_ms": 45
      }
    },
    {
      "id": "doc_004",
      "type": "code_reference",
      "sequence": 4,
      "content": "def main():\n    app = Flask(__name__)\n    app.register_blueprint(api_bp)\n    return app",
      "metadata": {
        "filePath": "src/main.py",
        "startLine": 5,
        "endLine": 8,
        "language": "python"
      }
    },
    {
      "id": "doc_005",
      "type": "text",
      "sequence": 5,
      "content": "Ich erstelle jetzt die Auth-Middleware und integriere sie in die App.",
      "metadata": { "format": "markdown" }
    },
    {
      "id": "doc_006",
      "type": "file_edit",
      "sequence": 6,
      "content": "from functools import wraps\nfrom flask import request, jsonify\nimport jwt\nimport os\n\nSECRET_KEY = os.environ.get('JWT_SECRET', 'dev-secret')\n\ndef authMiddleware(f):\n    @wraps(f)\n    def decorated(*args, **kwargs):\n        token = request.headers.get('Authorization', '').replace('Bearer ', '')\n        if not token:\n            return jsonify({'error': 'Token required'}), 401\n        try:\n            data = jwt.decode(token, SECRET_KEY, algorithms=['HS256'])\n            request.userId = data['userId']\n        except jwt.InvalidTokenError:\n            return jsonify({'error': 'Invalid token'}), 401\n        return f(*args, **kwargs)\n    return decorated",
      "metadata": {
        "filePath": "src/middleware/auth.py",
        "operation": "create",
        "language": "python"
      }
    },
    {
      "id": "doc_007",
      "type": "file_edit",
      "sequence": 7,
      "content": "from middleware.auth import authMiddleware\n\napp.register_blueprint(api_bp)\napp.register_blueprint(auth_bp)",
      "metadata": {
        "filePath": "src/main.py",
        "operation": "edit",
        "language": "python",
        "diff": {
          "oldString": "app.register_blueprint(api_bp)",
          "newString": "from middleware.auth import authMiddleware\n\napp.register_blueprint(api_bp)\napp.register_blueprint(auth_bp)",
          "startLine": 6,
          "endLine": 6
        }
      }
    },
    {
      "id": "doc_008",
      "type": "terminal_command",
      "sequence": 8,
      "content": null,
      "metadata": {
        "command": "pip install PyJWT",
        "exitCode": 0,
        "output": "Successfully installed PyJWT-2.8.0",
        "duration_ms": 3200,
        "permissions": ["network"]
      }
    },
    {
      "id": "doc_009",
      "type": "text",
      "sequence": 9,
      "content": "Die JWT Authentication-Middleware ist implementiert. Du kannst jetzt Routes schuetzen mit dem `@authMiddleware` Decorator:\n\n```python\n@app.route('/api/protected')\n@authMiddleware\ndef protectedRoute():\n    return jsonify({'userId': request.userId})\n```",
      "metadata": { "format": "markdown" }
    }
  ],
  "usage": {
    "promptTokens": 3200,
    "completionTokens": 1450,
    "totalTokens": 4650
  },
  "metadata": {
    "duration_ms": 8750,
    "toolCallCount": 2,
    "turnCount": 3
  }
}

5. Streaming-Format

Im Streaming-Modus wird jedes Dokument als Serie von Server-Sent Events uebertragen:

5.1 Event Types

Event Type Beschreibung
document_start Neues Dokument beginnt, enthaelt id und type
content_delta Text-Chunk fuer ein laufendes Dokument
tool_call_start Tool-Aufruf beginnt
tool_call_arguments Argumente des Tool-Aufrufs
tool_result Ergebnis des Tool-Aufrufs
document_end Dokument abgeschlossen
done Gesamte Antwort abgeschlossen, enthaelt usage

5.2 Event-Sequenz fuer ein Text-Dokument

event: document_start
data: {"id":"doc_001","type":"text","sequence":1}

event: content_delta
data: {"documentId":"doc_001","delta":"Ich analysiere "}

event: content_delta
data: {"documentId":"doc_001","delta":"zuerst die bestehende "}

event: content_delta
data: {"documentId":"doc_001","delta":"Projektstruktur..."}

event: document_end
data: {"documentId":"doc_001","finalContent":"Ich analysiere zuerst die bestehende Projektstruktur..."}

5.3 Event-Sequenz fuer einen Tool-Call

event: document_start
data: {"id":"doc_002","type":"tool_call","sequence":2}

event: tool_call_start
data: {"documentId":"doc_002","toolName":"read_file","toolCallId":"call_001"}

event: tool_call_arguments
data: {"documentId":"doc_002","arguments":{"target_file":"src/main.py"}}

event: tool_result
data: {"documentId":"doc_002","result":{"status":"success","data":"import os\n..."}}

event: document_end
data: {"documentId":"doc_002"}

6. TypeScript Interface-Definitionen

interface ChatResponse {
  id: string;
  conversationId: string;
  model: string;
  mode: "agent" | "plan" | "ask" | "debug";
  created: string;
  status: "completed" | "streaming" | "error";
  documents: Document[];
  usage: UsageInfo;
  metadata: ResponseMetadata;
}

type DocumentType =
  | "text"
  | "code_reference"
  | "code_block"
  | "file_edit"
  | "tool_call"
  | "terminal_command"
  | "plan"
  | "clarification"
  | "error"
  | "todo_update";

interface Document {
  id: string;
  type: DocumentType;
  sequence: number;
  content: string | null;
  metadata: Record<string, unknown>;
}

interface TextMetadata {
  format: "markdown" | "plain";
}

interface CodeReferenceMetadata {
  filePath: string;
  startLine: number;
  endLine: number;
  language: string;
}

interface CodeBlockMetadata {
  language: string;
  purpose: "new_code" | "example" | "suggestion";
}

interface FileEditMetadata {
  filePath: string;
  operation: "create" | "edit" | "delete" | "rename";
  language: string;
  diff?: {
    oldString: string;
    newString: string;
    startLine: number;
    endLine: number;
  };
}

interface ToolCallMetadata {
  toolName: string;
  toolCallId: string;
  arguments: Record<string, unknown>;
  result: {
    status: "success" | "error";
    data: unknown;
  };
  duration_ms: number;
}

interface TerminalCommandMetadata {
  command: string;
  workingDirectory?: string;
  exitCode: number;
  output: string;
  duration_ms: number;
  permissions: string[];
}

interface PlanMetadata {
  title: string;
  overview: string;
  todos: PlanTodo[];
  format: "markdown";
}

interface PlanTodo {
  id: string;
  content: string;
  status: "pending" | "in_progress" | "completed" | "cancelled";
  dependencies: string[];
}

interface ClarificationMetadata {
  questions: ClarificationQuestion[];
}

interface ClarificationQuestion {
  id: string;
  text: string;
  options: { id: string; label: string }[];
}

interface ErrorMetadata {
  errorCode: string;
  source: string;
  details: string;
}

interface TodoUpdateMetadata {
  todos: { id: string; status: string }[];
}

interface UsageInfo {
  promptTokens: number;
  completionTokens: number;
  totalTokens: number;
}

interface ResponseMetadata {
  duration_ms: number;
  toolCallCount: number;
  turnCount: number;
}

// Streaming Events
type StreamEventType =
  | "document_start"
  | "content_delta"
  | "tool_call_start"
  | "tool_call_arguments"
  | "tool_result"
  | "document_end"
  | "done";

interface StreamEvent {
  type: StreamEventType;
  documentId?: string;
  data: unknown;
}

7. Mapping: Cursor LLM Response → Document Types

Wie Cursor's roher LLM-Stream in Dokument-Typen umgewandelt wird:

LLM Output Stream
  ↓
Parser State Machine
  │
  ├─> Erkennt freien Text → type: "text"
  │     Akkumuliert bis naechster Segment-Beginn
  │
  ├─> Erkennt ``` mit startLine:endLine:filepath → type: "code_reference"
  │     Extrahiert: filePath, startLine, endLine, content
  │
  ├─> Erkennt ``` mit Language-Tag → type: "code_block"
  │     Extrahiert: language, content
  │
  ├─> Erkennt Tool Call im Response
  │     ├─> tool_name == "edit_file" → type: "file_edit"
  │     ├─> tool_name == "run_terminal_cmd" → type: "terminal_command"
  │     ├─> tool_name == "create_plan" → type: "plan"
  │     ├─> tool_name == "todo_write" → type: "todo_update"
  │     └─> alle anderen → type: "tool_call"
  │
  └─> Erkennt Fehler → type: "error"

Referenzen