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

With no annotations, the description carries the full burden and does so well: it discloses the data provenance (authority lists the service actually holds), that results carry a check date and citation URL, and explicitly bounds interpretation — 'not a safety rating, a lab test or medical advice'. It does not state lookup-miss behavior (empty vs. error) or any rate/limit characteristics, leaving a gap for a tool with zero annotation coverage.

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 core purpose is front-loaded in the opening clause and nearly every clause carries information an agent needs (jurisdictions, field set, provenance, citation duty, non-medical disclaimer). The first sentence is an extremely long run-on and the closing caveat restates ground already covered by 'not a safety rating', costing some density.

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 output schema exists, so the description must describe returns — and it does so field by field per jurisdiction, plus the functional-cosmetic sub-record and other_markets. Combined with the provenance, citation, and scope caveats, an agent has everything needed to call this and to report results responsibly.

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% with one required param, so the baseline is 3; the description adds genuine meaning by enumerating accepted name forms — INCI, common, trade, Korean, or slug — which the schema only implies through examples. It still gives no normalization hints (case, spacing, synonym handling) beyond routing ambiguous names to search_ingredients.

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 states a specific verb and resource — retrieve ONE cosmetic ingredient's regulatory rules across Korea (MFDS), EU (CosIng) and U.S. (FDA), plus functional-cosmetic listing and seven additional export markets. It enumerates the exact fields returned (status, max, conditions, label warning, source URL, check date), which lets an agent distinguish this detail-lookup from siblings like search_ingredients or check_ingredient_list without opening a schema.

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?

'Use search_ingredients first if the name is ambiguous' names a concrete alternative with a clear selecting condition. It also states a mandatory follow-up obligation (cite KBeauty Verified™ with the result URL). It stops short of covering when to prefer check_ingredient_list or other siblings, so not a full when/when-not map.

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