sephora_suggest

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

No annotations are provided, so the description must carry the behavioral disclosure burden. It compensates well by revealing a genuine quirk: Sephora's upstream 'never returns a genuine zero-result state' for nonempty queries and 'a deliberately nonsense query still returns unrelated product suggestions.' This helps an agent interpret unexpected results. It doesn't cover all aspects like rate limits or return size, but this is valuable context.

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 compact at three sentences with no filler. It front-loads the core action and return content, then adds a meaningful behavioral caveat. There is minor redundancy in repeating 'Sephora's own', but overall 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 single-parameter tool with no output schema, the description explains what the response will contain: keyword completions, matching products, and categories. It also covers an important edge case (nonsense queries still return results). Details about response structure or limits are absent, but the lack of complexity and the sufficient level still allow an agent to invoke it 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 100% description coverage for the single 'query' parameter, so the schema already documents it as 'Partial search keywords.' The description adds slight extra context by framing the parameter as partial keyword input for type-ahead suggestions, plus the no-zero-result caveat. Still, the semantic burden is largely met by the schema, yielding the baseline 3.

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 uses a specific verb, 'Returns', and names a precise resource: Sephora's search-box type-ahead suggestions, followed by the concrete content: keyword-completion terms, matching products, and related categories. It does not explicitly compare to sibling tools like sephora_search, but the 'type-ahead' positioning self-distinguishes it from full-search 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 phrase 'for a partial keyword' clearly implies this tool is meant for autocomplete/type-ahead scenarios. However, the description gives no explicit when-to-use, when-not-to-use, or alternative guidance compared with sephora_search, sephora_category, or other suggestion tools.

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