bestbuy_stores

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

No annotations are provided, so the description carries the responsibility for behavioral disclosure. It adds useful behavioral detail by saying the store data comes from Best Buy's own SEO store directory, that city matching is case-insensitive, and that state codes are limited to the 50 states plus dc and pr. It does not mention edge cases like missing cities or pagination, but the tool appears to be a read-only lookup, which the description supports.

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 first sentence is front-loaded with the tool's purpose and the required parameters are described immediately after. It is somewhat verbose due to the full list of state codes, but that list is useful and non-redundant because the schema has no enum. There is a slight redundancy between the first and second sentences, but overall the structure is efficient.

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 simple two-parameter lookup with no output schema, the description gives enough context to call the tool correctly: it states the input rules, the source of the data, and the fields the response contains. It does not define the exact output envelope or behavior when no stores match, but the missing detail is unlikely to prevent a successful call.

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 input schema only describes 'City name' and 'Two-letter state/territory code', so the description adds meaningful value by enumerating all valid state/territory codes and explaining that city is free text matched case-insensitively against the state's directory. This materially helps the agent construct a valid request without extra guessing.

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 opens with a specific verb and resource: 'Get Best Buy's physical stores in one city.' It then lists exactly what is returned, including name, address, phone, coordinates, rating, and hours, which makes the tool's action and scope immediately clear and distinguishable from product- or category-focused sibling tools.

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 gives clear context for when to use the tool: when physical store locations in a specific city are needed. It does not explicitly name alternatives or exclusions, but the 'physical stores' framing separates it from bestbuy_product, bestbuy_search, and similar siblings.

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