kyliecosmetics_search_suggest

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

No annotations exist, so the description carries the full burden. It adds useful behavioral context: the endpoint is credential-free, the storefront URL is fixed server-side, and returns are limited to product/collection/query suggestion categories. It omits output formatting, error behavior, and rate limits, but for a simple read-only suggest endpoint this is a reasonable level of disclosure.

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, each contributing: purpose, response categories plus source, and the fixed-URL caveat. No filler or redundant restatement of the tool name.

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?

The tool is simple (3 params, no output schema), and the description covers credential requirements, source, return categories, and server-side URL behavior. Missing details like exact JSON shape are not critical for a suggest endpoint, and the schema covers all parameters.

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% – q is described as 'Search query', limit has default/max details, and types lists allowed values. The description adds no parameter-specific syntax beyond what the schema already provides, so baseline 3 applies.

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 ('Get') and resource ('Kylie Cosmetics search suggestions'), enumerates the returned categories (products, collections, query suggestions), and notes the credential-free predictive search endpoint. The name plus description differentiates it from sibling kyliecosmetics_products/collections tools, which return full catalog data rather than suggestions.

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?

Implied usage – predictive search/autocomplete via a query parameter – is present, but the description never explicitly states when to choose this over alternatives or when not to use it. It does not name sibling kyliecosmetics_products or other suggest tools, so an agent must infer the use case from 'suggestions' and 'predictive search.'

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