goat_suggest

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

With no annotations provided, the description must carry the behavioral burden itself. It does add meaningful context: 'Credential-free public data' tells the agent no auth is required, and it discloses that the product count is upstream-fixed while collection count is controlled by limit. It does not address rate limits or error behavior, but for a read-only public autocomplete endpoint those omissions are worth a slight, minor gap.

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?

Three sentences, zero filler, and front-loaded: the core purpose autocomplete appears in the first few words, followed by the output composition, then usage context, then the access. Every sentence earns its place.

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 lightweight autocomplete utility this is well complete: the schema thoroughly captures both parameters and the description covers output kinds, the upstream product-count behavior, and the downstream purpose of the slug. The only residual gap is that no output schema exists and the description does not shape the product records or provide any pagination observation beyond the limit note, but this is a minor gap at this complexity.

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 description coverage is 100%, with query and limit thoroughly documented in the input schema (including the defaults, the max of 20, and the note that product count is unaffected). The description adds modest extra meaning by connecting the query to the output shape and explaining that the returned slug values are consumed by other endpoints, but the schema is doing most of the work.

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 first sentence states the verb ('Autocomplete'), the resource ('GOAT search'), and the two output kinds ('matching curated collections and matching products'), making the tool's scope concrete. It further differentiates the tool by noting the collections carry slug values consumed by sibling tools goat_collection and goat_search, which explains exactly how this tool fits into the GOAT family.

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 gives a clear when-to-use: 'Autocomplete a GOAT search' for partial queries, and specifically 'the way to discover collection slugs' accepted by other GOAT endpoints. It lacks explicit when-not-to-use guidance or named exclusions (e.g., goat_trending_searches, goat_search_facets), so it stops short of the strongest routing, but the slug-discovery purpose is concrete and actionable.

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