OECD SDMX Data Query

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

Annotations already declare readOnlyHint and idempotentHint; the description adds value by stating it is free, requires no authentication, and warns about potential large data volume when using default key, which are useful behavioral traits beyond metadata.

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 well-structured with an Args section and a preset dataset list, but it partially repeats information already in the schema (parameter descriptions), making it slightly less concise.

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?

The description does not explain the return format or structure of the query results; given there is no output schema, this omission leaves agents without guidance on how to interpret the response.

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?

The description supplements the 100% schema-covered parameters with examples, preset dataset names, and notes on default behavior (e.g., 'all' key may return large data), adding meaning beyond the schema descriptions.

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 queries OECD statistics (SDMX-JSON) and lists supported datasets, distinguishing it from the sibling tool ext_oecd_datasets which likely lists datasets rather than querying data.

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 provides clear context (free, no authentication) and examples of dataset usage, but lacks explicit guidance on when to use this tool versus other external data tools like ext_imf or ext_fred.

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