datasets_playstation_games_facets

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

With no annotations provided, the description bears full burden. It mentions returning 'terms aggregation counts' but does not disclose behavior like read-only nature, rate limits, pagination, or what happens with filters. This is insufficient for behavioral understanding.

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 concise with two sentences, front-loading the main purpose. It is efficient but could be more structured by separating the enum lists into bullet points for readability.

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 26 parameters and no output schema, the description lacks crucial context. It does not explain the output format (e.g., bucket structure for each facet), what 'terms aggregation counts' means operationally, or how filters interact. This is inadequate for 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%, so baseline is 3. The description adds value by explicitly listing the allowed facet enum values and price_tier enum values, which go beyond the schema's descriptions. This helps the agent understand valid inputs.

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 it performs faceting (terms aggregation counts) on the PlayStation games dataset, listing all available facet fields. This distinguishes it from search and item retrieval siblings 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 aggregating counts rather than searching for games, but does not explicitly state when to use this tool versus alternatives or when not to use it. No exclusions or context are provided.

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