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Glama

Scope Reusable Data by Licence

find_by_licence
Read-onlyIdempotent

Find datasets published under a specific licence to assess compliance and reuse options. Enter an exact licence name or alias to get a summary of all matching datasets.

Instructions

Return all datasets with the given licence, summarised. Use to enumerate what's available under a specific licence for compliance/reuse scoping.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
licenceYesExact licence name or supported alias, e.g. 'Creative Commons Attribution 4.0'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.2

TDQS

A4/5.0
Behavior3/5

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

The annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds that results are 'summarised' and licence matching is by exact name or alias, but does not go far beyond what the schema and annotations already convey. No contradiction exists.

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 concise sentences with no filler. It front-loads the action and outcome, then adds the relevant use case, making every sentence earn 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?

With only one required parameter, no nested objects, and an output schema present, the description covers the essential purpose and usage context. The word 'summarised' is slightly vague, but the output schema can reasonably carry the return-format details.

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%, and the description adds little beyond the schema's examples and 'exact licence name or supported alias' note. The parameter meaning is clear, but the description does not enrich it significantly.

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 states a specific verb and resource: 'Return all datasets with the given licence, summarised.' It clearly identifies the licensing scope and differentiates itself from broad search tools like search_datasets by focusing on a specific licence.

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?

'Use to enumerate what's available under a specific licence for compliance/reuse scoping' gives a clear context and intent. It does not explicitly mention when not to use it or name alternatives, but the use case is unambiguous.

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