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

With no annotations, the description carries the full burden and does disclose the computed output surface: price per kg delta, protein per ruble, KBJU per portion and per 100g, glaze type, sugar presence, lab rating. 'На лету' implies a non-mutating on-the-fly computation, but error behavior for unknown or ambiguous curd names is not covered.

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?

One front-loaded sentence with the verb and scope first, then the metric list. The enumeration is long but each item names a distinct computed comparison, so it earns its place.

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?

No output schema exists, so the description must sketch return content, and it does so thoroughly across price, protein efficiency, nutrition, glaze authenticity, sugar and lab rating. Only edge-case handling (item not found, duplicate inputs) is left unspecified.

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 parameter is fully documented, including case-insensitive matching and an example. The description's '2 to 5' count adds a mild constraint already implied but not stated in the schema, so baseline 3 applies.

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?

Opens with a specific verb and resource ('Сравнить от 2 до 5 глазированных сырков на лету') and then enumerates exactly what the comparison computes. It is clearly distinguishable from the siblings, which search, rank, profile single items, or analyze E-codes rather than comparing a set.

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 '2 to 5 items' range is an implicit usage constraint, but nothing states when to prefer this over get_curd_dossier or get_top_curds. Usage must be inferred from the list of computed metrics rather than from explicit routing guidance.

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