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lakehouse_update_definition

Update a lakehouse definition by uploading file parts from inline content or a directory path, ensuring the lakehouse configuration matches the provided definition.

Instructions

Update a lakehouse's definition (long-running). Accepts definition parts inline or a directory path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
partsNoArray of definition parts to upload
lakehouseIdYesThe lakehouse ID
workspaceIdYesThe workspace ID
partsDirectoryPathNoPath to a directory containing definition files

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv2.8.0

TDQS

A4.2/5.0
Behavior4/5

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

The description discloses a key behavioral trait, 'long-running', which is not captured by the readOnlyHint/destructiveHint annotations. It also indicates two modes of input (inline parts or directory path), which helps the agent understand expected invocation shape. It does not contradict the annotations, and the safety profile (not read-only, not destructive) is consistent with an update operation.

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?

The description is two sentences with no filler. It front-loads the action and immediately gives the critical behavioral note ('long-running'), followed by the two input modes. Every phrase earns its place.

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?

For a 4-parameter tool with full schema coverage and annotations covering the safety profile, the description is reasonably complete: it states the action, the long-running nature, and the two supported input strategies. The only notable omission is what the caller receives after initiating the long-running operation, but the absence of an output schema makes this a moderate gap rather than a critical one.

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

Parameters4/5

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

Schema description coverage is 100%, which already documents each parameter. The description adds meaning by explaining the relationship between 'parts' and 'partsDirectoryPath': these are two alternative ways to provide definition content. This goes beyond the schema's isolated property descriptions and helps the agent decide how to populate the optional fields.

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 opens with a specific verb and resource: 'Update a lakehouse's definition'. It clearly distinguishes this from sibling tools like lakehouse_get_definition (read vs. write), lakehouse_update (general update vs. definition-specific update), and other resource update_definition tools. The parenthetical '(long-running)' adds useful scope.

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

Usage Guidelines3/5

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

The description implies the use case: this tool is for updating a lakehouse's definition, especially when definition parts are provided inline or via a directory. However, it does not explicitly state when to prefer this over lakehouse_update, nor does it mention alternatives or exclusions. The guidance is present but only inferred.

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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