get_str_data

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

No annotations are provided, so the description must carry the behavioral transparency burden. It discloses data content but does not describe operational behavior such as read-only semantics, response format, default scoping, pagination, or the effect of optional parameters. It adds only limited behavioral insight beyond the data categories listed.

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 a single, tightly written sentence that front-loads the domain ('Airbnb/short-term rental market data') and then specifies the key metrics. There is no filler or redundancy; every word contributes meaning.

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 straightforward two-parameter data retrieval tool, the description lists the data categories and scope, giving reasonable context. However, with no annotations and no output schema, the agent lacks information about return structure, error behavior, or default assumptions. It is adequate but not comprehensive.

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 descriptions for both parameters (city and neighborhood), and schema description coverage is 100%. The description adds little beyond the schema, only reinforcing the city-level scope and listing data fields. Since the schema handles parameter semantics, a baseline score 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 clearly identifies the resource (Airbnb/short-term rental market data) and specifies the key data dimensions (nightly rates, occupancy, superhost stats) at city level. It uses a specific verb ('get') and concrete fields, making the tool's purpose readily understandable. It does not explicitly differentiate from the sibling get_market_summary, so it falls just short of a 5.

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 the tool is for short-term rental market data needs, which gives some usage context. However, it does not state when to prefer this tool over alternatives such as get_market_summary, search_listings, or list_locations, nor does it mention exclusions or prerequisites. Usage is only implied by the data-content description.

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