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OverviewDiscussions(1)Admin

Draft a Fabric IQ ontology from the plan (nothing deployed)

ontology_draft
Read-only

Drafts a Fabric IQ ontology (preview) from the plan: entity types with keys, relationship types and bindings. Requires workspace and source. Returns JSON with a summary (the rule behind each key and link), the binding checklist, a Turtle file for Import ontology and the item definition parts. Changes nothing; create_ontology creates the item. Errors: {error, kind, hint}.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "workspace": "<workspace>",
      "source": "<source>"
    },
    "name": "ontology_draft"
  }
}

Input Schema

NameRequiredDescriptionDefault
keysNoPrimary keys replacing the inferred ones. Default: inferred. Example: {"order_items": ["order_id", "line_no"]}.
nameNoName of the ontology in the draft. Default "ontology". Example: "shop_ontology".ontology
schemaNoSchema in the source. Default "dbo".dbo
sourceYesLakehouse, warehouse or SQL database, name or id.
tablesNoExact table names to include. Default all.
confirmedNoRelationships the user confirmed, added to the plan. Default none. Example: [{"source": "orders", "source_cols": ["ship_to_id"], "target": "addresses", "target_cols": ["address_id"]}].
workspaceYesFabric workspace, name or id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "title": "Result",
-      "type": "string"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "title": "ontology_draftOutput",
-  "type": "object"
-}New value: +null
  2. Changed7 schema fields changed
    • addedInput schema / properties / confirmed / description
      Added value: +"Relationships the user confirmed, added to the plan. Default none. Example: [{\"source\": \"orders\", \"source_cols\": [\"ship_to_id\"], \"target\": \"addresses\", \"target_cols\": [\"address_id\"]}]."
    • addedInput schema / properties / keys / description
      Added value: +"Primary keys replacing the inferred ones. Default: inferred. Example: {\"order_items\": [\"order_id\", \"line_no\"]}."
    • addedInput schema / properties / name / description
      Added value: +"Name of the ontology in the draft. Default \"ontology\". Example: \"shop_ontology\"."
    • addedInput schema / properties / schema / description
      Added value: +"Schema in the source. Default \"dbo\"."
    • addedInput schema / properties / source / description
      Added value: +"Lakehouse, warehouse or SQL database, name or id."
    • addedInput schema / properties / tables / description
      Added value: +"Exact table names to include. Default all."
    • addedInput schema / properties / workspace / description
      Added value: +"Fabric workspace, name or id."
  3. First observed

TDQS

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description reinforces it with 'Changes nothing' while going further: it enumerates the returned payload (summary with the rule behind each key and link, binding checklist, Turtle file, item definition parts) and the error contract {error, kind, hint}. That is real behavioral context an agent cannot get from the annotations or schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four short, front-loaded sentences covering purpose, requirements, return shape and error shape with essentially no filler. Slightly dense in the return-value sentence where four artifacts are packed together, but nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 7-parameter, read-only drafting tool with no output schema, the description supplies the missing return-value and error-shape information and confirms no side effects. An agent has everything needed to decide to call it and to interpret the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents all seven parameters including defaults and examples. The description only restates the two required inputs ('workspace and source') and gestures at the plan; it adds no syntax or format detail beyond what the schema provides, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Drafts a Fabric IQ ontology') plus the outputs it produces (entity types with keys, relationship types and bindings), so the agent knows exactly what the call yields. It also explicitly distinguishes itself from the sibling create_ontology, which is the deployment counterpart.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Names the alternative explicitly ('create_ontology creates the item') and signals the draft-vs-deploy split, plus prerequisite 'Requires workspace and source'. What is missing is an explicit 'use this first when you want to preview/validate before deploying' statement, but the routing is clear enough to act on.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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