get_dimension_values

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool lists all valid codes and labels and supports optional NUTS filtering. However, it does not mention edge cases such as behavior when nuts_level is supplied for a non-'geo' dimension, ordering, pagination, or error conditions. This is adequate but not rich.

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 one sentence, front-loaded with the core action ('List all valid codes and labels'), followed by a concise optional modifier. Every word earns its place; there is no fluff or repetition.

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?

For a simple listing tool with three parameters, full schema coverage, and an output schema present, the description is complete. It states the purpose, the resource targeted, and the optional filtering behavior. No additional context seems necessary for an agent to invoke it 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 description coverage is 100%, so the schema already documents all parameters. The description adds little beyond what the schema provides—the mention of NUTS filtering for 'geo' mirrors the schema's own parameter description. It gets the baseline score of 3 because it does not harm understanding but also does not add meaningful extra context.

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 opens with a specific verb ('List') and names the exact resource ('valid codes and labels for a specific dataset dimension'). It also mentions the optional NUTS regional filtering, which clearly distinguishes this tool from siblings like query_dataset or get_dataset_info. The function and scope are 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 clearly indicates the tool is for retrieving dimension code-label pairs and specifies when NUTS filtering can be applied (for 'geo'). It does not explicitly name alternatives or state exclusions, but the context is clear enough that an agent can infer when to use it. A slightly more explicit 'use this instead of get_dataset_info for dimension values' would push it to 5.

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