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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds genuinely useful behavior: the return is a terms aggregation count, and the filters are inherited from search to scope the aggregation. Pagination caps are stated but largely duplicate the schema.

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-loaded and readable, but it repeats the facet allowed values twice (as 'Facet enum:' and again in the 'facet:' sentence) and re-states the page constraint verbatim from the schema. Two of its sentences are largely redundant with structured fields.

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 a 100%-covered schema, an output schema, and annotations, the description needs only to frame the operation, which it does. The remaining gap is a positive when-to-use signal versus search, but nothing required to invoke it correctly is missing.

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 13 parameters including the facet enum and page/page_size constraint. The description restates the facet values and page rule rather than adding meaning (e.g. what 'market' means beyond crawl provenance, or how facets interact with q). Baseline 3 is correct.

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?

States a specific verb and resource: 'Returns terms aggregation counts for the Starbucks store directory', and immediately names the facet dimension it aggregates over. An agent can distinguish it from its siblings (search, item, nearby) without opening the 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?

Explicitly routes the agent: use datasets_starbucks_stores_search to search, and notes this tool accepts the same filters 'to scope the aggregation'. This makes the search-vs-facet split clear, though it never states the positive case for facets (e.g. 'use when you need counts/breakdowns, not individual stores').

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