datasets_airbnb_search

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

Despite no annotations, the description provides good behavioral transparency. It explains that thin cells are suppressed, enrichment-derived fields may remain empty if coverage is low, FX conversion is approximate, and guest_favorite_pct is an observed lower bound. It does not mention rate limits or authentication, but overall it is transparent about data characteristics.

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 long but well-structured. It front-loads the core purpose and then logically explains parameters, return fields, and behavioral notes. Every sentence adds value, though it could be slightly more concise.

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 no output schema, the description adequately explains return fields and key behaviors (aggregate-only, thin cell suppression, enrichment-derived fields). It covers sort enum values and parameter constraints implicitly. It is complete for a search tool, though it does not explicitly mention pagination constraints beyond what the schema provides.

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 description adds significant meaning beyond the parameter schema. It explains the group_by enum values in detail, including when they stay empty, and clarifies the meaning of return fields like median_price_usd, guest_favorite_pct, and avg_person_capacity. With 100% schema coverage, this exceeds the baseline.

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 the tool searches the Airbnb markets dataset and returns aggregate short-term-rental market rollups. It explicitly says 'Aggregate-only: each row is a market cell, never an individual listing,' which distinguishes it from tools like airbnb_search that may return individual listings.

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 explains what the tool does but does not explicitly state when to use it versus sibling tools like airbnb_search or datasets_airbnb_facets. It implies aggregate market analysis use case but lacks direct guidance on selection.

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