datasets_airbnb_facets

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

No annotations provided. Description mentions 'suppressed distribution counts' hinting at data suppression but doesn't explain behavioral traits like auth needs, rate limits, or response details. Adds value with suppression context but incomplete.

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?

Two concise sentences with enum lists. Front-loaded with purpose. No fluff, every sentence adds 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?

Missing output structure details (e.g., what the distribution counts look like, how group_by affects output). Given no output schema, description should clarify return format for a faceted dataset.

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%. Description adds value by explaining that filters honor search semantics and that min_listings raises suppression floor, going beyond schema descriptions. Enhances understanding of parameter interactions.

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?

Description clearly states it facets the Airbnb markets dataset and returns suppressed distribution counts, distinguishing it from search tools that return individual listings. The verb 'facet' and resource 'Airbnb markets dataset' are specific.

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?

Implies use when aggregated counts are needed, honoring same filters as search, but lacks explicit when-to-use vs alternatives like datasets_airbnb_search. The reference to search filters provides context.

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