wendys_store_menu

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does well by stating the tool is credential-free, requires no session or account, and returns real data from a cold, cookie-less request. It also explains what the tool does NOT do (does not compute combo prices like /wendys/item) and what it does include (store-specific promotional items). However, it doesn't describe the response format, pagination, or potential failure modes, which would be useful for a complete behavioral picture.

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 description is a single, information-dense paragraph that front-loads the core purpose ('Get one Wendy's restaurant's full priced/offered menu') before diving into differentiators and technical details. Every sentence adds value: the contrast with /wendys/item, the credential-free confirmation, and the store_id sourcing guidance. It's slightly long but justified given the need to distinguish from several sibling tools and convey the authentication-free nature.

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 tool's simplicity (one parameter, no output schema, no nested objects), the description is quite complete. It covers what the tool returns, how it differs from siblings, and how to obtain the required parameter. The only minor gap is the lack of information about the response structure or any potential errors, but for a single-parameter read-only tool, this is a minor omission. The credential-free confirmation is particularly valuable context.

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 the single parameter store_id. The description adds value by explaining the store_id is a numeric store id and gives concrete examples of where to obtain it (from /wendys/nearby's stores[].store_id or /wendys/restaurant's store_id). This goes beyond the schema's basic description and helps the agent source the correct identifier.

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 clearly states the tool retrieves one Wendy's restaurant's full priced/offered menu, with specific verb 'Get' and resource 'one Wendy's restaurant's full priced/offered menu'. It explicitly distinguishes itself from sibling tools like /wendys/menu and /wendys/item, noting it returns real local pricing and store-specific promotions rather than generic national listings. This makes the purpose unambiguous and differentiates it from similar menu-related 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 explicitly contrasts this tool with GET /wendys/item and /wendys/menu, explaining that this tool provides real local pricing including combo bundle prices that /wendys/item deliberately does not compute. It also states the tool is credential-free and requires only a store id, giving clear context for when to use it. The mention of 'Found via static analysis of Wendy's official Android app' and 'confirmed credential-free' provides additional usage confidence.

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