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

With no annotations, the description carries the full burden and does well: it discloses data sources, the absence of safety judgments, mandatory attribution, and a non-commercial-use restriction. What is less clear is the shape of what comes back (a description of the service vs. a dataset of sources), though the enumerated topics imply it.

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?

Purpose is front-loaded in the first clause and the most important constraint (no safety ratings) appears early. There is some duplication — the 'not a safety rating' framing and the attribution/citation rule are each restated — which adds length without new information.

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 zero-parameter, no-annotation, no-output-schema informational tool, nothing an agent needs is missing: purpose, scope limits, provenance, and the obligations that come with using the data are all present.

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 tool takes zero parameters, so no parameter guidance is required; baseline is 4. The description correctly implies a no-argument, informational call.

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 precisely what the tool covers: what KBeauty Verified™ is, the provenance of its data (MFDS, CosIng, FDA plus 7 export markets), and explicitly what it does not do (no safety ratings, no lab tests, no medical advice). This clearly separates it from data-returning siblings like lookup_ingredient or check_ingredient_list.

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?

"Call this first if unsure" gives a concrete routing rule for orientation, and the attribution/non-commercial rules tell the agent when it must surface licensing text with results. It does not explicitly contrast against siblings such as official_sources or ask_kbeauty_verified, which would be the natural question for a caller.

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