grubhub_offers

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

With no annotations provided, the description carries the full behavioral disclosure burden. It does this well by explaining that empty lists are common and legitimate, and by detailing the amount field semantics for free-item offers. It does not mention pagination, errors, or authentication, but for a read-style offers endpoint the provided behavioral context is substantial.

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 front-loaded with the core action and resource, then adds high-value interpretive details. No sentence is filler; the offer-type examples, badge equivalence, empty-list guidance, and amount semantics all earn their place without making the description bloated.

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 there is no output schema and no annotations, the description compensates strongly: it states the result is a list, describes offer categories, explains the common empty case, and clarifies ambiguous amount fields. The required parameters are already fully documented in the schema, so nothing essential for invoking this tool correctly is 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 description coverage is 100%, so the schema already documents restaurant_id, latitude, and longitude. The description adds no input-parameter meaning beyond that baseline; its field-level notes about amount.value and amount.order_minimum concern the response, not the request parameters.

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 one Grubhub restaurant's currently active promotions.' It further distinguishes itself from likely siblings like grubhub_restaurant_menu and grubhub_restaurant_reviews by naming the exact data domain (promotions) and even the site badge it corresponds to.

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 when to use the tool: when you need currently active promotions for a single restaurant, and it clarifies that an empty list is a normal result rather than an error. However, it never explicitly names alternatives or states when to prefer a sibling tool like grubhub_restaurant or grubhub_restaurant_menu.

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