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

Annotations already declare the operation as read-only and open-world. The description adds that data comes from Best Buy's own directory and lists the returned fields, but it does not disclose rate limits, pagination, or authentication needs, so it provides only modest additional behavioral context.

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?

Two tight sentences: the first front-loads what the tool returns and its source; the second precisely defines the two parameters. No wasted words.

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 the simple lookup nature, 100% schema coverage, and the presence of an output schema, the description supplies enough context. It could mention whether all stores in a city are returned, but that is a minor gap.

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%, but the description goes beyond the schema by giving examples (e.g., il) and clarifying that city is free text matched against the state's own directory. This helps the agent understand that state and city work together to scope the lookup.

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 the tool returns Best Buy physical store locations in a single city, lists the fields returned (name, address, phone, coordinates, rating, hours), and names the data source (Best Buy's own directory). This clearly distinguishes it from sibling tools like bestbuy_product or bestbuy_search, which handle products, not stores.

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 the intended scenario: retrieving store locations for a given city and state. It does not explicitly state when not to use it or name alternatives, but no sibling tool serves the same purpose, so the context is clear.

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