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

Annotations already declare the operation is read-only, idempotent, closed-world, and non-destructive. The description adds useful behavioral context beyond that: the catalog contains 5000+ items, queries should use concrete terms, and results include SKU, unit price, wholesale price, stock availability, and a link. It does not describe matching logic or ranking, but the added return-field disclosure is valuable because no output schema exists.

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 definition is two tight sentences. It front-loads the catalog scope and search intent, then lists query guidance and return fields without wasted wording.

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?

Because there is no output schema, the description's explicit list of returned fields (SKU, prices, stock, link) is important and well covered. The catalog scope and query expectations are also covered. Minor gaps remain around result ranking and matching behavior, but the definition is otherwise complete for a search tool whose annotations and schema cover safety and parameters.

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 query, limit, and in_stock_only with examples. The description reinforces that the query should be specific terms (brand, line, grit, diameter, type) but adds little parameter meaning beyond what the schema provides, making the baseline 3 appropriate.

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 gives a specific verb ('Ищет') and resource (the catalog of «Абразив Эксперт») with a concrete scope: abrasives, polishing pastes/discs, spray guns, paints, and painting materials, 5000+ items. An agent can immediately tell this is full-catalog product search, distinct from single-product retrieval or analog lookup.

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 description does imply usage by saying the query should contain specific words such as brand, line, grit like P120, diameter like 150, or type, and gives examples. However, it never states when to use this tool versus siblings such as get_product, find_analogs, or recommend_for_task, nor does it name any exclusion conditions.

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