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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=false, so the safety profile is covered. The description adds genuine behavioral context beyond them: what the response contains and the caveat that the size filter reflects the model's size range rather than available inventory — a misuse trap the annotations cannot express.

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?

Three dense sentences, front-loaded with purpose before caveats, and each sentence earns its place: catalog scope, return contents, and the size/stock distinction. No filler or restatement of the name.

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?

An output schema exists, so return-value detail is optional, yet the description still summarizes it helpfully. Combined with siblings (get_product, check_availability, find_city) and schema-documented defaults like city_id and limit, the agent has enough to call it correctly; only the relationship between country/city filtering is left implicit.

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 60%; the schema's own 'size' description ('Size as on the website') is ambiguous, and the description meaningfully augments it by clarifying it is a model size range, not stock. It adds no meaning for the undocumented sort, brand, price_min, and price_max parameters, so it compensates for the most critical gap but not all of them.

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 opens with a specific verb+resource+scope: searching the 'kari catalog (shoes, clothing, bags, accessories)' with filters. It also names what the result contains (price, size range, website link), so an agent knows exactly what this tool produces and how it differs from product-detail siblings.

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?

It resolves the most dangerous ambiguity explicitly — 'sizes is the size range of the model, not stock: check stock with get_product or check_availability' — which is both a when-not condition and a named alternative. It does not, however, say when to prefer this search over a direct get_product lookup by name, leaving that choice to inference.

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