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

With no annotations, the description carries the full behavioral burden and does it well: answers are grounded only in KBeauty Verified™ records with sources, each result carries url/cite fields that must be cited, and the tool is explicitly not a safety rating, lab test, or medical advice. This discloses provenance, output obligations, and limits that no structured field provides.

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?

Front-loaded with the core purpose and scope; the language and grounding constraints follow logically. The branding/source URL and attribution paragraph are somewhat boilerplate but do encode a real citation obligation, so little is truly wasted.

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 one-parameter, no-output-schema, no-annotation tool, the description covers everything an agent needs: what to send, what language behavior to expect, where answers come from, which result fields to cite, and what the tool must not be treated as.

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 single `question` parameter has 0% schema description coverage, and the description compensates by establishing that it is free-text, may be in English or Korean, and that the answer language mirrors the question. It does not state length/format constraints, but the semantic meaning is well conveyed.

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 ('Ask a question') and a concrete resource domain (K-beauty ingredients, products, sunscreen filters, recalls, KR/EU/US rules). The natural-language Q&A framing implicitly separates it from lookup-style siblings like lookup_ingredient and search_ingredients, but no sibling is named explicitly.

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?

Gives clear usage context: ask in English or Korean, and the answer language follows the question language. Scope topics are enumerated, but there are no explicit exclusions or pointers to the alternative tools (lookup_ingredient, check_ingredient_list) for structured lookups.

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