mcp-fabric-api

lakehouse_get_definition

Read-only

Retrieve a lakehouse's definition and save the definition files to a chosen output directory, making the structure available for review or reuse.

Instructions

Get the definition of a lakehouse (long-running). Writes definition files to the specified output directory.

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": {
      "workspaceId": "<workspaceId>",
      "lakehouseId": "<lakehouseId>",
      "outputDirectoryPath": "<outputDirectoryPath>"
    },
    "name": "lakehouse_get_definition"
  }
}

Input Schema

Name	Required	Description
`lakehouseId`	Yes	The lakehouse ID
`workspaceId`	Yes	The workspace ID
`outputDirectoryPath`	Yes	Directory path where definition files will be written

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.8.0Sep 6, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already signal readOnlyHint=true and destructiveHint=false. The description adds meaningful behavioral context beyond those annotations: the operation is long-running and it writes definition files to a user-supplied output directory, which is a useful side effect for the agent to expect.

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

Conciseness5/5

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

Two short, purposeful sentences. The primary action and long-running nature are front-loaded, and the file-writing behavior earns its place in the second sentence. No filler.

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

Completeness4/5

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

With all required parameters documented in the schema and annotations covering safety, the description is largely complete for invocation. It could be more explicit about return behavior or how completion is signaled, but the long-running note and output-file side effect cover the most important operational expectations.

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?

The input schema already documents all three parameters with 100% coverage. The description only echoes outputDirectoryPath ('writes definition files to the specified output directory') and does not add new parameter-level detail such as format, default, or directory behavior.

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?

The description uses a specific verb ('Get'), a clear resource ('the definition of a lakehouse'), and adds the behavioral qualifier 'long-running' plus the output side effect of writing definition files. This makes it easy to distinguish from sibling tools like lakehouse_get or lakehouse_update_definition even without opening the schema.

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

Usage Guidelines2/5

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

The description states what the tool does but gives no guidance on when to choose it over alternatives such as lakehouse_get for simple metadata or lakehouse_update_definition for modifying definitions. No prerequisites, exclusions, or alternative-selection conditions are mentioned.

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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