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Glama

search_datasets

Search Kaggle datasets by keyword, user, or file type, and sort results to find relevant data for your projects.

Instructions

Search Kaggle datasets

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mineNo
pageNo
userNo
limitNo
queryNo
sort_byNohottest
file_typeNoall

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.0.0

TDQS

C2.3/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It only says 'Search Kaggle datasets,' which implies a read-only operation but reveals nothing about result format, pagination behavior, sorting semantics, filtering behavior, or whether the search is global or restricted to the user's own datasets.

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

Conciseness2/5

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

The description is short, but this is under-specification rather than conciseness. 'Search Kaggle datasets' contains a single phrase and provides no operational detail, so it does not earn its place as a useful tool definition.

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

Completeness1/5

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

For a 7-parameter tool with no annotations, no output schema, and no parameter descriptions, this description is severely incomplete. An agent cannot determine how to construct a valid search, what defaults apply, how pagination works, or what the response will contain, so correct invocation is essentially guesswork.

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

Parameters1/5

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

The schema has 0% description coverage across 7 parameters, and the description adds no parameter meaning whatsoever. The agent is left completely in the dark about what query, mine, user, page, limit, sort_by, and file_type actually control. A tool with this many parameters requires at least some high-level explanation of their roles.

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

Purpose4/5

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

The description states a clear verb and resource: 'Search Kaggle datasets.' This is specific enough to distinguish it from sibling tools like upload_dataset or delete_dataset, but it does not explicitly differentiate it from list_my_datasets or list_dataset_files, which are related listing operations.

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?

No usage guidance is provided. The description does not explain when to use search_datasets versus sibling tools such as list_my_datasets, dataset_details, or list_dataset_files, nor does it mention any prerequisites or search scenarios.

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