siftio.marouane-kouskous.workers.dev

{
  "name": "list_datasets",
  "kind": "answer",
  "impl": "imperative",
  "description": "List every dataset currently loaded in the user's local SiftIO vault, with row counts and column schemas. Call this first to discover what is available.",
  "inputSchema": {
    "type": "object",
    "properties": {},
    "required": []
  }
}

{
  "name": "list_samples",
  "kind": "answer",
  "impl": "imperative",
  "description": "List the demo datasets bundled with SiftIO that can be loaded into the vault. Call this when list_datasets comes back empty — the vault starts empty in a fresh browser session, and these are the only datasets you can load yourself. Load them with load_sample and query them with the tools rather than fetching the files directly: querying runs in DuckDB over the whole vault, supports joins across datasets, and is recorded in the user's audit log.",
  "inputSchema": {
    "type": "object",
    "properties": {},
    "required": []
  }
}

{
  "name": "load_sample",
  "kind": "act",
  "impl": "imperative",
  "description": "Load one bundled demo dataset into the local vault by file name, taken from list_samples. This registers query_<table> and describe_<table> tools for it. Only bundled samples can be loaded this way; the user adds their own files by dropping them on the page.",
  "inputSchema": {
    "type": "object",
    "required": [
      "file"
    ],
    "properties": {
      "file": {
        "type": "string",
        "description": "A file name from list_samples, e.g. \"transactions.csv\"."
      }
    }
  }
}

{
  "name": "run_sql",
  "kind": "answer",
  "impl": "imperative",
  "description": "Run a read-only SQL SELECT against the local DuckDB vault. Tables are named by the `table` field from list_datasets. Use this to join across datasets. At most 1000 rows are returned. The result echoes the `sql` that ran — quote it when you report a number, so the reader can see what was counted. Amounts may be negative where a dataset records refunds; excluding them is a different question, so say which you did.",
  "inputSchema": {
    "type": "object",
    "required": [
      "sql"
    ],
    "properties": {
      "sql": {
        "type": "string",
        "description": "A single SELECT statement."
      }
    }
  }
}

{
  "name": "render_chart",
  "kind": "act",
  "impl": "imperative",
  "description": "Run a read-only SELECT and draw the result in the SiftIO viewport so the user can see it. Use after run_sql when a picture helps. The result echoes the `sql` that ran, alongside `columns` and `rows`.",
  "inputSchema": {
    "type": "object",
    "required": [
      "sql",
      "kind"
    ],
    "properties": {
      "sql": {
        "type": "string"
      },
      "kind": {
        "type": "string",
        "enum": [
          "bar",
          "line",
          "scatter",
          "table"
        ]
      },
      "x": {
        "type": "string",
        "description": "Column for the x axis."
      },
      "y": {
        "type": "string",
        "description": "Column for the y axis."
      }
    }
  }
}

{
  "name": "save_view",
  "kind": "act",
  "impl": "imperative",
  "description": "Pin a named query and chart to the user's board so it survives after this conversation ends.",
  "inputSchema": {
    "type": "object",
    "required": [
      "name",
      "sql",
      "kind"
    ],
    "properties": {
      "name": {
        "type": "string"
      },
      "sql": {
        "type": "string"
      },
      "kind": {
        "type": "string",
        "enum": [
          "bar",
          "line",
          "scatter",
          "table"
        ]
      },
      "x": {
        "type": "string"
      },
      "y": {
        "type": "string"
      }
    }
  }
}

{
  "name": "eject_dataset",
  "kind": "act",
  "impl": "imperative",
  "description": "Remove a dataset from the local vault. The user is asked to confirm first.",
  "inputSchema": {
    "type": "object",
    "required": [
      "table"
    ],
    "properties": {
      "table": {
        "type": "string"
      }
    }
  }
}