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

Annotations already mark readOnlyHint=true, and the description adds that it returns an nsfw_score and can include detailed results when detail=1. It also discloses the per-call cost, but it does not explain the score scale, threshold, or what the detailed result contains.

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 purpose is front-loaded, but the first two sentences repeat the same statement in English and Korean, wasting tokens. The detail=1 and cost notes are useful but do not fully compensate for the redundancy.

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?

With no output schema, the description gives minimal return information (nsfw_score, optional detailed result) but omits the interpretation or range of the score and the shape of the detailed output. Still, for a simple single-URL detector, the core invocation requirements are 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?

Schema description coverage is 100%, so the schema already documents image_url and detail sufficiently. The description's mention of detail=1 effectively restates the schema's '세부 판정 결과 포함 여부' rather than adding new semantic meaning.

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 operation ('Detect whether an image contains NSFW content') and a specific output ('return an nsfw_score'), with an explicit definition of NSFW as violent or sexually explicit. This clearly distinguishes it from image-related siblings like face_detection or image_similarity.

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 intended use is implied by the operation itself, but there is no explicit when-to-use or when-not-to-use guidance, and no alternatives are named. An agent must infer when this tool is appropriate among many image-processing siblings.

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