datasets_producthunt_makers_facets

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns distribution counts and uses search filters. It does not mention authentication, rate limits, or side effects, but for a read-only facet this is adequate.

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 clear sentences, front-loading the purpose and providing essential details without extraneous information.

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 simple facet tool with full schema coverage and no output schema, the description adequately covers the dataset, facet fields, and filter behavior. It could optionally describe the output format but is complete enough.

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 context by linking parameters to search filters and listing facet enum values, but the schema itself already documents the parameters comprehensively.

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 that the tool facets the Product Hunt makers dataset and returns distribution counts. It specifies the dataset id and the available facet fields, distinguishing it from search and item retrieval tools.

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 use when distribution counts are needed rather than items, stating that it honors the same filters as search. However, it does not explicitly provide when-not-to-use guidance or name alternatives among siblings.

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