foodpanda_restaurant_reviews

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

With no annotations present, the description carries the burden of explaining behavior. It discloses the sampled nature, the curated source for SEO rich results, scaling behavior, and the possibility of an empty result. It doesn't mention rate limits or side effects, but it is clearly a read operation and the caveat about emptiness adds real transparency.

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 front-loads the core action and information returned, then adds scope and caveats. It is a little wordy, but every sentence carries distinct information about the return type, sourcing, volume, and failure mode, so no part is wastefully redundant.

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?

With no output schema, the description compensates by enumerating the returned fields and clarifying edge cases such as scaling size and empty results. It doesn't specify ordering or exact rating format, but for a sample-read endpoint the description is complete enough to guide a correct call.

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?

The input schema already provides 100% description coverage for both parameters, including the provenance of 'code' (from /foodpanda/search) and the default for 'market'. The description adds no extra parameter-level semantics, so the baseline of 3 is appropriate.

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 uses a specific verb 'Get' and identifies the resource as 'a sample of one foodpanda restaurant's customer reviews', then enumerates the exact fields (author name, publish date, review text, rating). This clearly distinguishes it from sibling tools like foodpanda_restaurant or foodpanda_restaurant_menu, which cover restaurant details and menu instead.

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?

It explicitly contrasts the curated sample with 'the full review corpus a logged-in customer would see in the app', signaling when not to use this tool. It also describes dynamic behavior (number scales with popularity, can be empty), giving the agent a clear expectation for when to invoke it.

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