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

No annotations, so the description carries the burden; it discloses the return payload, flags that the result is 'free', and notes the servability status. It does not cover auth requirements, rate limits, or failure behavior, so it stops short of full disclosure.

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?

Front-loads the resource definition and packs the return contents into one dense clause list, with workflow guidance in the trailing sentences. Everything earns its place, though the long enumerative first sentence is heavier than strictly necessary.

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?

No output schema exists, so the description must describe returns itself, and it does so thoroughly (dimensions, codes, labels, frequencies, coverage, countries, servability). Combined with the pre-call workflow note and id provenance, an agent has everything needed 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?

One parameter at 100% schema coverage sets a baseline of 3, and the description adds meaningful provenance beyond the schema by telling the agent the id originates from search_datasets. It does not add format or validation nuance beyond the schema example.

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?

Names a specific resource (the published structure of one dataset) and enumerates exactly what it contains: dimensions with member codes and labels, frequencies, period coverage, ISO3 countries, servability. An agent can distinguish this from get_series and get_table without opening any schema.

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?

Gives explicit sequencing ('Call this before get_series to learn the codes to send') and names the sibling that supplies its input ('Dataset ids come from search_datasets'). Both when-to-use and where-the-argument-comes-from are stated.

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