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

With no annotations, the description carries the full load — and it does substantial work: it discloses what data is returned (ingredient list with source, regional prohibited/limited/conditional status across Korea MFDS, EU CosIng, FDA plus 7 export markets), a key limitation (labels omit amounts, so limits cannot be verified from the list), and an explicit scope disclaimer (not a safety rating, lab test, or medical advice). Missing only failure behavior for an invalid or unknown slug.

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?

Content is front-loaded with the payload description before provenance and citation obligations. It runs long and mixes data description, licensing, and disclaimers, but each element serves a provenance-dependent tool rather than padding.

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?

No annotations and no output schema, so the description must cover behavior alone — it explains the returned content, its provenance, the key limitation on interpreting limits, and the required citation using fields (`url`/`cite`) that hint at the return shape. Only the not-found/error path is left unaddressed.

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?

One required parameter with 100% schema description coverage — the schema already explains the slug is the trailing part of a search-result URL. The description adds no syntax, format, or example detail about the slug beyond that, 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?

Opens with a concrete verb-and-resource statement — one K-beauty product with its full ingredient list plus per-region (Korea/EU/U.S.) prohibition and limit status — which is specific enough to separate it from search_products and lookup_ingredient. It never names those siblings, though, so the differentiation is inferred rather than stated.

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 implies a follow-up flow (the schema notes the slug comes from a search result, and the text mandates citing the returned url), but it never explicitly says 'call search_products first' or when to prefer check_ingredient_list/lookup_ingredient instead. The attribution requirement is the only explicit usage instruction.

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