adidas_store

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

With no annotations, the description carries the full burden, and it delivers: it discloses the error behavior ('An unknown store_id returns a not-found error'), states the data is 'normalized,' and lists the exact response content — the key uncertainties for a single-id GET. It could go further (rate limits, coordinate format, meaning of 'status'), but the not-found disclosure is genuine value beyond the name and 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?

Four short sentences, each earning its place: instant action, return payload, parameter provenance, and error behavior. The most important information (what it does and what it returns) is front-loaded, with zero filler or repetition of schema content.

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 low-complexity tool (1 required param, no output schema, no annotations), the description is nearly complete: the field enumeration substitutes for the missing output schema, the id-source hint covers the workflow, and the error case is handled. Minor gaps like coordinate format and phone formatting are the only omissions, and they don't block correct invocation.

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%, so the baseline is 3. The description adds real value beyond the schema by clarifying that store_id is numeric (the schema only says 'string', which could lead an agent to pass a slug or name) and by pinning the exact source field (stores[].id). This extra precision justifies a 4.

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+resource ('Get an Adidas store') and precisely enumerates the returned payload (name, status, phone, address, coordinates, hours, in-store services). It is clearly distinct from siblings: the reference to an 'adidas-stores response' differentiates this detail-by-id tool from the plural listing tool, and 'retail store' separates it from adidas_product/adidas_search.

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?

Usage context is implied through the store_id provenance: 'taken from an adidas-stores response's stores[].id field' tells the agent this tool is meant to be called after adidas_stores, with an id obtained from that listing. However, there is no explicit statement of when to choose this over alternatives, and no exclusions or fallback guidance — the routing is left to inference.

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