describe_schema

Describe Schema

What it answers

Return the semantic layer: marts, columns, invariants, canonical payers, and the tools YOU can call (the same list tools/list returns for you, never a wider catalog). Compact by default (a manifest: marts + a name + one-line summary per tool, under ~8K chars). Fetch one section with describe_schema(section='<mart>') / section='tools' / section='invariants'. Pass verbosity='full' for the previous full payload. Agents call this first to learn the surface, then fetch the section or tool they need.

Inputs

include_examples

boolean · optional

default: true

include_invariants

boolean · optional

default: true

limit

any · optional

default: null

mart_name

any · optional

default: null

offset

integer · optional

default: 0

section

any · optional

default: null

verbosity

string · optional

one of: compact, full

default: "compact"

Call it

From an agent: connect the Vlada MCP once (one click for Claude, ChatGPT, Cursor, VS Code) and ask in plain English; the agent selects describe_schema when the question fits. From code: the same tool over REST with an API key. The schema endpoint needs no key.

curl -X POST https://api.vladahealth.com/v1/tools/describe_schema \
  -H "Authorization: Bearer $VLADA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{}'

curl https://api.vladahealth.com/v1/tools/describe_schema/schema      # the JSON schema, no auth
# MCP endpoint (Streamable HTTP): https://mcp.vladahealth.com/mcp

What comes back

Typed rows plus provenance on every answer: the public source file, its vintage, the methodology, and a response_hash you can replay. Prove and replay tools turn any number into a re-runnable receipt. A number the data cannot support comes back as “not in the data”, never as zero.

Output schema

{
 "$defs": {
  "Quality": {
   "description": "Row-level quality signal. All flags precomputed at build time\n(stored on the gold mart) and passed through here.",
   "properties": {
    "is_outlier": {
     "default": false,
     "title": "Is Outlier",
     "type": "boolean"
    },
    "is_ghost_candidate": {
     "default": false,
     "title": "Is Ghost Candidate",
     "type": "boolean"
    },
    "n_similar_rates": {
     "default": 0,
     "title": "N Similar Rates",
     "type": "integer"
    },
    "confidence": {
     "default": 1,
     "title": "Confidence",
     "type": "number"
    }
   },
   "title": "Quality",
   "type": "object"
  },
  "Source": {
   "description": "Cell-level provenance. Every served value traces back here.\n\n`snapshot_id` is the Iceberg snapshot the tool read from. Two calls\nat the same snapshot MUST produce byte-identical responses —\nthat's the content-addressed caching guarantee.",
   "properties": {
    "table": {
     "title": "Table",
     "type": "string"
    },
    "rate_id": {
     "anyOf": [
      {
       "type": "string"
      },
      {
       "type": "null"
      }
     ],
     "default": null,
     "title": "Rate Id"
    },
    "source_files": {
     "items": {
      "type": "string"
     },
     "title": "Source Files",
     "type": "array"
    },
    "snapshot_id": {
     "anyOf": [
      {
       "type": "integer"
      },
      {
       "type": "null"
      }
     ],
     "default": null,
     "title": "Snapshot Id"
    }
   },
   "required": [
    "table"
   ],
   "title": "Source",
   "type": "object"
  }
 },
 "properties": {
  "value": {
   "default": null,
   "title": "Value"
  },
  "unit": {
   "anyOf": [
    {
     "type": "string"
    },
    {
     "type": "null"
    }
   ],
   "default": null,
   "title": "Unit"
  },
  "vintage": {
   "anyOf": [
    {
     "type": "string"
    },
    {
     "type": "null"
    }
   ],
   "default": null,
   "title": "Vintage"
  },
  "source": {
   "$ref": "#/$defs/Source"
  },
  "methodology": {
   "anyOf": [
    {
     "type": "string"
    },
    {
     "type": "null"
    }
   ],
   "default": null,
   "title": "Methodology"
  },
  "quality": {
   "$ref": "#/$defs/Quality"
  },
  "invariants_applied": {
   "items": {
    "type": "string"
   },
   "title": "Invariants Applied",
   "type": "array"
  },
  "caveats": {
   "items": {
    "type": "string"
   },
   "title": "Caveats",
   "type": "array"
  },
  "response_hash": {
   "default": "",
   "title": "Response Hash",
   "type": "string"
  },
  "semantic_version": {
   "default": 1,
   "title": "Semantic Version",
   "type": "integer"
  },
  "tool_version": {
   "default": "unknown",
   "title": "Tool Version",
   "type": "string"
  },
  "explanation": {
   "anyOf": [
    {
     "type": "string"
    },
    {
     "type": "null"
    }
   ],
   "default": null,
   "title": "Explanation"
  },
  "status": {
   "default": "complete",
   "title": "Status",
   "type": "string"
  },
  "refusal": {
   "anyOf": [
    {
     "additionalProperties": true,
     "type": "object"
    },
    {
     "type": "null"
    }
   ],
   "default": null,
   "title": "Refusal"
  },
  "failure": {
   "anyOf": [
    {
     "additionalProperties": true,
     "type": "object"
    },
    {
     "type": "null"
    }
   ],
   "default": null,
   "title": "Failure"
  },
  "as_of": {
   "anyOf": [
    {
     "type": "string"
    },
    {
     "type": "null"
    }
   ],
   "default": null,
   "title": "As Of"
  },
  "freshness_state": {
   "default": "unknown",
   "title": "Freshness State",
   "type": "string"
  }
 },
 "title": "SchemaResponse",
 "type": "object"
}

Sources behind it

Known limits

No gaps recorded for this tool. Absence of a recorded gap is not a claim of complete coverage; the answer itself says what it covers.

As of the 2026-09-19 build of the served surface · machine-readable catalog · the live server may run a different version; the schema endpoint above is authoritative for what is deployed.