datasets_airbnb_item

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

No annotations provided, so description carries full burden. It discloses the aggregate nature, expected data content, and the 404 error for suppressed countries. It does not mention auth or rate limits, but for a simple read operation this is acceptable.

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?

Three sentences, each adding essential information: purpose, data details, and error condition. Front-loaded, no fluff.

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 one parameter and no output schema, the description is fairly complete. It explains the tool's output and error handling. Minor omission: could mention that the response is per country and what happens if country is invalid, but sufficient.

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% with a description. The description adds value by explaining the dataset id and the scope of data returned per country, enriching understanding beyond the schema's parameter description.

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 it retrieves an Airbnb market for a country, listing specific data fields (headline supply, Superhost share, ratings, etc.) and distinguishes it from siblings like datasets_airbnb_search by emphasizing 'aggregate-only' and the dataset id 'airbnb-markets'.

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 usage for aggregate country-level data but does not explicitly state when to use this tool versus siblings like datasets_airbnb_search or individual airbnb_* tools. It provides good context but lacks explicit when-to-use or when-not-to-use guidance.

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