datasets_starbucks_stores_nearby

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

No annotations are provided, so the description carries the burden. It discloses that this queries a stored dataset rather than live data, that results are nearest-first, and that it can return every store in the radius (unlike the capped live endpoint). It does not mention pagination behavior or whether results include distance values, but the core behavioral distinction from the live endpoint is well covered.

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?

Three sentences with no filler. The core function and required inputs are front-loaded, and the comparison to the live endpoint is a single useful sentence. Every sentence earns its place.

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 read-only lookup tool with 100% schema coverage and no output schema, the description covers the essential behavior, required inputs, and the key distinction from the live endpoint. It could mention pagination defaults or that results are from a static dataset, but the schema already covers page/page_size defaults. The description is complete enough for an agent to select and invoke the tool 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 that lat, lon, and radius_m are required and that radius_m defines the search radius, but it does not add meaning beyond the schema for optional parameters like page, page_size, amenity, or country. Baseline 3 is appropriate.

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 finds nearby stored Starbucks stores within a radius of a point, sorted nearest first, from a specific dataset. It names the resource (stored Starbucks stores from dataset `starbucks-stores`), the operation (find nearby), and the key inputs (lat, lon, radius_m). It also distinguishes itself from the live /starbucks/stores endpoint, which is a sibling-like alternative.

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 explicitly says lat, lon, and radius_m are required, and contrasts this tool with the live /starbucks/stores endpoint, noting the live one caps at 50 near a point while this one queries the full grid-tiled directory. This gives an agent clear when-to-use and when-not-to-use guidance relative to a known alternative.

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