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

Goes well beyond the safety-oriented annotations (readOnly/idempotent/non-destructive) by disclosing return composition, ordering logic (best-match then cheapest, from two searches), and a detailed set of filtering rules: colour/fabric enforcement, garment-kind matching by title and category, gendered results, kids only on request, exclusion of adult/fetish/costume listings, dedup of repeats, and removal of junk/bait pricing.

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 before the usage examples and the detailed filtering/ranking rules, and each clause carries real information. It is dense and somewhat run-on, and the trailing list of filter rules could be tightened, but the length is broadly justified by the tool's complexity.

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?

There is no output schema, so the description carries the full burden of explaining returns — and it does: eBay listings, ranking order, search links for other shops, and a Facebook Marketplace search phrase. Combined with the detailed filtering rules, an agent has enough to select and invoke this 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?

With 100% schema coverage the baseline is 3, and the description genuinely adds precedence semantics: a price or size mentioned in the natural-language query is only used when max_price/size are not explicitly passed, and occasion is deliberately excluded from the search. It also confirms adult/kids/gender filtering behavior that the schema does not express.

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+resource ('Find clothes that match a description') and clearly distinguishes itself from the text-vs-image sibling (wardrobeconnect_find_clothes_by_image) by framing the input as a natural-language description. It also names the concrete output source (eBay listings in the Clothing, Shoes and Accessories category).

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 a clear trigger condition ('Use when the user describes a piece of clothing they want') with several representative example queries, including a fully natural one. It does not explicitly name a sibling alternative or a when-not-to-use condition (e.g. image input belongs to find_clothes_by_image), leaving that to inference from the tool name.

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