{
  "name": "retrieve_context",
  "description": "Retrieves high-precision context for answering a user query using Hybrid Search and RRF.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "query": {
        "type": "string",
        "description": "The user's natural language query."
      },
      "filters": {
        "type": "object",
        "description": "Metadata filters (e.g., source, author, date range).",
        "properties": {
          "source": { "type": "string" },
          "tags": { "type": "array", "items": { "type": "string" } }
        }
      },
      "top_k": {
        "type": "integer",
        "description": "Number of chunks to retrieve (default: 10).",
        "minimum": 1,
        "maximum": 50
      }
    },
    "required": ["query"]
  }
}

{
  "name": "semantic_search",
  "description": "Performs a raw vector similarity search without RRF or hybrid fusion. Use for exploration.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "vector_query": {
        "type": "string",
        "description": "The text to embed and search."
      },
      "threshold": {
        "type": "number",
        "description": "Minimum similarity score (0.0 to 1.0).",
        "default": 0.7
      }
    },
    "required": ["vector_query"]
  }
}