quince_search

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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it delivers: it reveals the underlying Algolia search index, AND-combination semantics, the relevance/popularity ranking when no filters are supplied, typo-tolerant rather than exact-match search, and the important edge case that zero matches return a well-formed empty result instead of an error. These are non-obvious behaviors an agent needs to set expectations correctly.

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 a single dense paragraph, but every sentence earns its place: it covers scope, source index, combination semantics, valid-value provenance, ranking behavior, and edge cases. It is front-loaded with the core purpose and does not waste words, though the length is substantial enough that it could be slightly restructured for faster scanning.

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 10-parameter search tool with no output schema and no annotations, the description is remarkably complete: it explains how to browse versus search, where to obtain valid facet values, how filters combine, and what happens on zero matches. The main gap is that it does not describe the shape of a successful response, which would have been useful given the absence of an output schema.

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%, so the baseline is 3, but the description adds semantic value beyond the schema: it explains that q, department, category, material, color, size, min_price, and max_price are all optional and combine as an AND, clarifies that q can coexist with facet filters, and points to the exact source fields for valid values. This helps an agent construct valid parameter combinations.

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 ('Search or browse Quince products') and immediately anchors it to quince.com's public Algolia index. It clearly distinguishes this tool from sibling catalog tools by contrasting it with 'some other families' search/category-browse split' and referencing quince-categories and quince-navigation, so an agent can tell them apart.

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 explicitly states when to use this tool versus alternatives: free-text q can be combined with any facet filter, every field can be omitted to browse the full catalog by relevance, and quince-navigation's browsable slugs are offered as a 'curated, hierarchical alternative' to the flat category facet. It also points to quince-categories for valid facet values, giving concrete routing guidance.

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