datasets_playstation_games_facets

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

No annotations are provided, so the description carries the burden. It discloses that the operation returns terms aggregation counts (a read-only analytical operation), but does not mention pagination, multiple facet support, default behavior, or any error conditions. Some value is added beyond the trivial, but it is not deep.

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 sentences total, with front-loaded purpose. The enum lists make it longer but are necessary for informing valid values. There is minor redundancy with schema enums, but overall it is efficient and well-structured.

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?

With 26 parameters and no output schema, the description is too minimal. It does not explain how facets interact with filters, whether multiple facets can be requested, or what the response structure looks like beyond 'terms aggregation counts'. This is insufficient for such a complex tool.

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 each parameter described. The description repeats the facet enum and price_tier enum, which are already in the schema, but adds no new semantic information about parameters. Baseline of 3 applies since schema handles param semantics.

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 states a specific verb ('Facet') and resource ('PlayStation games dataset'), and clarifies the outcome as 'Returns terms aggregation counts'. This clearly distinguishes it from sibling tools like datasets_playstation_games_search and datasets_playstation_games_item.

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 aggregation/faceting rather than search or item retrieval, but does not explicitly name alternatives or state when not to use it. It provides the facet enum, giving some context for when this tool is appropriate, but lacks exclusionary guidance.

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