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

Annotations already declare readOnlyHint and openWorldHint. The description adds real value beyond them: filters combine as AND, and a zero-match query returns a well-formed empty result rather than an error — non-obvious behavioral facts an agent needs.

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?

Purpose is front-loaded and most sentences carry signal, but the aside 'unlike some other families' search/category-browse split' is tangential and the em-dash-heavy styling makes it denser than needed.

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?

An output schema exists and annotations cover the safety profile, so the description only needs to cover invocation semantics — which it does: optional params, AND combining, browse fallback, facet value sources, and empty-result behavior.

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 the baseline is 3. The description adds the AND-combination semantics across q/department/material/color, which the schema does not state; the facet-value provenance note largely duplicates schema text, and it omits how category/size/min_price/max_price combine.

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?

States a specific verb+resource ('Search or browse Quince's product catalog') and the mechanism/data source ('through its own public Algolia search index'). An agent can distinguish this from siblings like quince_product or quince_categories immediately.

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?

Explains when to use free-text q vs facet filters vs omitting everything to browse by relevance ranking, and points to quince_categories for valid facet values. It lacks an explicit 'use X instead when...' routing against sibling tools, but the usage context is clear.

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