List data sources, licenses, and attribution rules

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds valuable context about the specific sources (World Bank WDI, IMF via DataMapper, DBnomics fallback, ECB, FRED disabled), which informs the user about what the tool will report—context not captured in 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 a single, well-structured sentence that front-loads the primary purpose and packs all essential information (source list, coverage, license, attribution) without redundancy or filler.

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 no parameters and no output schema, the description is fully complete: it states exactly what the tool lists (sources, licenses, attribution) and the scope (official StatCite sources). No additional context is necessary.

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 tool has zero parameters, so the baseline of 4 applies. The description adds no parameter details, but none are needed; the schema already trivially covers all parameters.

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 lists data sources, licenses, and attribution rules, with a specific verb ('List') and resource ('sources behind StatCite'). It distinguishes itself from sibling data-fetching tools by focusing on metadata and citation rules.

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 when to use the tool (when one needs to know available sources, their coverage, licenses, and attribution lines) and what it does not do (it does not retrieve data). It lacks explicit alternatives or exclusions, but the context is clear enough to guide selection.

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