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Get DataLens Trino resource preset

datalens_trinoclusters_resource_preset_get
Read-onlyIdempotent

Retrieves details of a cluster machine resource preset, including cores and memory, using a preset ID and cloud environment ID.

Instructions

One size of a cluster's machines: its cores and its memory.

Experimental in the DataLens API and written from its document: not measured.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
resource_preset_idYesId of the resource preset.
cloud_environment_idYesThe cloud environment the presets are of.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.122.1

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, covering the safety profile. The description adds one genuinely useful disclosure – that the API is 'Experimental... not measured' – but it is vague about what the caller should expect (unstable output? no guarantees?). It neither states return format nor contradicts the annotations.

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?

Two short sentences with no padding. The structural weakness is that the leading sentence describes the concept rather than the tool's action, so the front-loaded information is not the operational framing an agent needs first.

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

Completeness3/5

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

For a two-parameter read tool with full schema coverage and no output schema, coverage is adequate to avoid errors, but the description omits the action, the relationship to the list sibling, and any concrete meaning of the 'experimental/not measured' caveat.

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 description coverage is 100% for both required parameters (resource_preset_id, cloud_environment_id), so the schema already documents them. The description adds no syntax, format, or scoping detail beyond it, so the baseline 3 applies.

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

Purpose3/5

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

The description defines the resource ('one size of a cluster's machines: its cores and its memory') but never states the action the tool performs. The verb 'get' lives only in the name/title, so the description reads as an entity definition rather than a retrievable operation. An agent can infer the purpose, but it is not stated directly.

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?

There is no guidance on when to call this versus the clearly related sibling datalens_trinoclusters_resource_presets_list, nor any mention of prerequisites such as needing a valid cloud_environment_id. The description provides no usage context at all.

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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