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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description usefully adds that results are aggregate market rollups rather than individual listings, but says nothing about freshness, suppression, or response shape beyond what the schema implies.

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?

A single front-loaded sentence with no filler. It is appropriately terse, though the brevity leaves room for one clarifying clause that would have earned higher value.

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 12-parameter aggregate tool, the description is thin, but the schema is fully documented and an output schema exists, so return values need no explanation. What is missing is orientation on what the rollups contain and how they differ from the sibling item/facets tools.

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 all 12 parameters (pagination caps, sort enums, group_by dimensions, suppression floor) are fully documented in the schema. The description adds no parameter-level meaning, which is the expected baseline when the schema does the work.

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?

Names a specific verb (search) and resource (Airbnb markets dataset), and the parenthetical '(aggregate market rollups)' distinguishes it from listing-level siblings like datasets_airbnb_item and airbnb_search. It does not name those siblings explicitly, so differentiation requires inference.

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?

There is no statement of when to use this rather than datasets_airbnb_item, datasets_airbnb_facets, or datasets_airbnb_nearby, and no prerequisites or exclusions. The agent must infer usage purely from the resource name.

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