nomis_get_data

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

No annotations provided, but the description fully discloses behavior: returns flat records with named dimension values, numeric obs_value, and record count. It explains the dimensions mapping format and that measures is usually required. No hidden or contradictory information.

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?

Very concise: one sentence for purpose, a focused block explaining the key parameter, and a final sentence on return format and prerequisite tools. No fluff, front-loaded with essential information.

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?

With an output schema present, the description does not need to detail return values, but it still mentions the flat records, dimension values, and obs_value. It also provides essential context on prerequisite tools, making it complete for a data retrieval tool.

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 0%, but the description thoroughly explains the `dimensions` parameter with a full example and syntax rules. The `dataset_id` is self-explanatory. However, the `select` parameter is not described, leaving a gap despite overall strong compensation.

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 retrieves observations from a Nomis dataset (simple JSON). It specifies the resource (observations) and action (retrieve), distinguishing it from siblings like nomis_get_dataset which retrieves dataset structure.

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?

Explicitly instructs to use nomis_get_dataset and nomis_dimension_options / nomis_geography_search first to find correct codes before calling this tool. This provides clear when-to-use and when-not-to-use guidance, effectively differentiating from related tools.

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