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

Adds substantial context beyond the readOnlyHint=false / openWorldHint=true annotations: the labeled output ('AI preview, not a real photo, not exact fit'), the consent requirement, reuse of photo_tryon's content policy and rate limits, unsupported categories, and the no-storage guarantee. These are the operational details an agent needs before invoking a generative tool.

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-loads the core action, then chains the return format, consent requirement, policy pointer, and exclusions in compact clauses. Dense but every sentence carries a distinct operational fact; nothing is redundant with the title or schema.

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 two-image generative tool with no output schema, the description covers the essential ground: what is produced (labeled AI preview), the consent gate, content restrictions, and data handling. An agent has everything it needs to invoke it correctly.

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 67%, and the description compensates usefully by disambiguating the two inputs — the outfit comes from the second photo and the person from the first — which maps directly onto the outfit_* vs person_* parameter pairs. It also explains the consent flag's meaning, though it says nothing about the category enum or the URL-vs-base64 alternatives.

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 and resource — placing an outfit from a second photo onto the person in the first photo — with clarifying examples of acceptable outfit sources (product shot, flat lay, worn). This clearly separates it from the single-photo sibling photo_tryon, so an agent can distinguish the two without opening either 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?

Gives explicit preconditions (consent=true for photo 1, adult consent), points to the shared content policy and daily limits of photo_tryon, and lists exclusions (lingerie, swimwear, see-through). It never states positively when to prefer this over photo_tryon, but the two-photo framing makes the selection condition reasonably clear.

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