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

Annotations already declare readOnly, idempotent, non-destructive behavior, so the safety profile is covered. The description adds one genuinely useful behavioral fact — that the result pairs a technology with suitable products — which matters because there is no output schema. It says nothing about result size, ranking, or what happens when a task is out of scope (e.g., non-abrasive domains).

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?

Two compact sentences: a colon-delimited list of examples followed by the single actionable instruction. Nothing is padded, and the input instruction is placed last where it is most likely to be acted on. Slightly list-heavy but justified since the examples define scope.

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 one-parameter, read-only recommendation tool with no output schema, the description covers scope and hints at the return shape. It is still thin on what the agent gets back (products with prices? links? cart-ready?) and gives no routing guidance among the many sibling lookup tools. Adequate but with real gaps.

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 100% and the single `task` parameter already carries two worked examples with a length constraint. The description adds breadth by naming five more task domains, which helps the agent bound what counts as an acceptable free-text task, but it adds no syntactic or formatting guidance beyond the schema. Baseline 3 is 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 states a specific capability: selecting a technology and matching products for a customer's task, and enumerates concrete task domains (glass scratches, body polishing, sanding, wood/furniture, spray-gun choice). An agent understands the resource being produced. It does not, however, contrast itself with siblings such as search_products or find_analogs, so the differentiation is left implicit.

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?

"Опишите задачу своими словами" implies the usage pattern: free-text task description rather than structured filters. But there is no explicit when-to-use vs. when-not, and no mention of when to prefer find_analogs or search_products instead. Usage is inferable rather than stated.

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