datasets_steam_games_facets

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

No annotations are provided, so the description is the only source. It discloses that the tool returns terms aggregation counts and lists valid facet, price_tier, and review_tier enums. However, it does not explain how the many filter parameters interact with the aggregation, return format, or any limitations.

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 compact and front-loaded with purpose, but the phrase 'for the Steam games dataset' is repeated in the first two sentences, adding minor redundancy. The enum list is long but necessary.

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?

Despite having a large set of filter parameters and no output schema, the description does not explain how filters relate to the facet aggregation or what the response structure looks like. An agent would be able to call the tool but lacks context on combining filters, multiple facets, or pagination, making it incomplete for a 27-parameter 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?

All 27 parameters are fully described in the schema (100% coverage), so baseline is 3. The description adds no extra semantic detail; its enum lists (facet, price_tier, review_tier) duplicate the property descriptions in the schema already.

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 explicitly states it facets the Steam games dataset and returns terms aggregation counts, which is a specific verb+resource+outcome. It distinguishes from sibling search tools by focusing on facet aggregations.

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?

No explicit when-to-use vs alternatives; the description just says 'Facet the Steam games dataset' without explaining when to choose this over datasets_steam_games_search. Usage is implied by the term 'facet' and the list of facet enums, but no exclusions or alternatives are named.

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