grubhub_restaurant_reviews

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 enumerating what each review contains, noting the 1-5 star histogram, explaining sort behavior, and flagging the upstream discrepancy between search ratings and written reviews. It does not cover response envelope or pagination metadata, but the schema already documents page/page_size.

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 purpose and then expands into return contents, sort options, and a caveat. It is slightly redundant in that the first sentence and the start of the second sentence both announce the same return payload, but the detailed field list and the upstream-systems note earn their place, especially given the absence of an output schema.

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 read-only retrieval tool with no output schema and no annotations, the description is largely complete: it states the returned entities, the review fields, the histogram, the sort options, and a data-quality caveat. It could additionally describe the histogram's exact shape or response structure, but the provided information is sufficient for an agent to select and invoke the tool correctly.

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 baseline is 3. The description largely repeats what the schema already says about sort values, defaults, and restaurant_id provenance, and it adds no new parameter-level meaning beyond that. It does provide helpful context about review fields, but that is output semantics rather than parameter semantics.

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 reviews and rating histogram.' This clearly distinguishes the tool from siblings like grubhub_restaurant, grubhub_restaurant_menu, and grubhub_search, and it states the exact scope (one restaurant) and output (reviews plus histogram).

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 clearly establishes when this tool is relevant: when you need written Grubhub customer reviews and a rating histogram for a single restaurant. It also provides a useful caveat that the written-review corpus and the headline rating in search are separate upstream systems, which helps set expectations, though it does not explicitly name alternative tools or state when not to use it.

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