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

Annotations only cover readOnly/openWorld; the description adds substantive interpretation context beyond them: the country-vs-market (true country vs crawl provenance) distinction and the crucial note that an empty schedule means 'not published for this market', not 'closed'. This directly prevents an agent from misreading empty fields as store closure.

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 what the tool does and then layers in interpretation guidance; every sentence except the 'store_number: ...' fragment carries non-obvious information. The trailing param restatement is redundant against the schema, a minor blemish.

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?

An output schema exists, so return shape need not be described. The remaining risk area — how to read empty schedule/amenities fields and country vs market — is explicitly addressed, leaving nothing essential for a correct call 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 coverage is 100% and the sole parameter is already documented in the schema. The description mostly restates the store_number semantics ('Starbucks store number, e.g. 101-54') without adding new format or constraint meaning, so baseline 3 applies.

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 one stored Starbucks store by its store number'), anchors it to dataset id 'starbucks-stores', and gives a concrete example (`101-54`). This distinguishes it cleanly from the search sibling.

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 to 'datasets_starbucks_stores_search to search the Starbucks store directory', which is the key alternative. The condition for choosing this tool (you already have a store number) is implied rather than spelled out, so it falls just short of the explicit when/when-not framing.

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