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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, establishing a safe read operation. The description adds value by explicitly listing the returned fields (name, descriptions map, supportedLocales, defaultLocale, category id, update dates) and noting multilingual support, which goes beyond 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.

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

The description is two sentences, front-loaded with the purpose, and then lists return fields. Every sentence provides essential information with no fluff or redundancy. It is concise and well-structured.

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

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

Given the tool's simplicity (one parameter, strong annotations, no output schema), the description is fully adequate. It explains the resource, the input, and the return payload in enough detail for an agent to select and invoke the tool correctly.

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

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

Schema coverage is 100%, so the baseline is 3. However, the description adds the practical hint that the id is 'e.g. the dataSourceId from a view', giving an agent useful context about where to obtain the UUID beyond the schema's generic 'Dataset (datasource) UUID'. This small addition raises the score.

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

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

The description clearly states the tool fetches multilingual metadata for one Statbel dataset by its UUID, specifying 'by its id' and referencing 'dataSourceId from a view'. This distinguishes it from sibling tools like list_datasets, which enumerates datasets, making the purpose specific and unambiguous.

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

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

The description implies usage when a specific dataset UUID is known, especially mentioning 'the dataSourceId from a view' as a source. It provides clear context for when to use the tool, though it does not explicitly name alternatives or state when not to use it. This aligns with 'clear context, no exclusions'.

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