goat_search_facets

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

With no annotations provided, the description carries the full transparency burden and does so well. It discloses that categories, colors, genders, conditions, brands, and years are read live from GOAT's API, that product_types and activities come from a maintained list, that brands is truncated and flagged via brands_truncated, and that the data is credential-free and public.

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 front-loaded with a one-sentence summary and then provides dense, necessary details about data freshness, maintained lists, brand truncation, and authentication. Every clause earns its place, and there is no filler.

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 zero-parameter tool with no output schema, the description is complete enough: it states what the tool returns, which values are live versus maintained, how to interpret brands_truncated, and that no credentials are needed. An agent has everything required to select and invoke this tool correctly.

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 has zero parameters, so there is nothing that needs semantic explanation; the baseline of 4 applies. The description adds value by enumerating the filter parameters whose accepted values are returned, but it cannot add input-parameter meaning beyond that since no inputs exist.

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 opens with a specific verb and resource: 'Get GOAT search facet values.' It then clarifies exactly what is returned: accepted values for goat_search's filter parameters. This clearly distinguishes it from the goat_search tool itself and other goat_* siblings.

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 makes the relationship to goat_search explicit by stating this returns accepted values for goat_search's filter parameters, so the intended usage context is clear. It does not explicitly name alternatives or give 'when not to use' guidance, but it does provide important caveats like the brands_truncated flag that affect how results should be consumed.

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