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

With no annotations present, the description carries the disclosure burden. It does explain the two behavioral modes: aggregate results without region, and regional median/rank with region. It does not disclose output format, units, or behavior for unknown or invalid regions, so transparency is adequate but incomplete.

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 description is one front-loaded sentence stating the core metric, the default output, and the parameterized variant with no redundant 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?

For a low-complexity tool with one optional fully documented parameter and no output schema, the description covers both invocation modes and the kind of result returned. It lacks only minor details such as exact return format or the number of regions shown, which do not block correct invocation.

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?

The schema already documents that region accepts a Russian name or slug. The description adds meaningful semantics by explaining that supplying region changes the result from nationwide aggregate to the specific region's median and rank, going beyond what the schema provides.

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 clearly identifies the resource (price per kilometer by bus in Russia) and the expected outputs: nationwide median, cheapest and most expensive regions, and with a region parameter the regional median and rank. It does not explicitly contrast it with sibling tools such as cheapest_destinations, so it is clear but lacks explicit sibling differentiation.

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 implies when to use the tool: when bus price-per-kilometer statistics are needed, either for the whole country or for a specific region. However, it gives no explicit when-not-to-use guidance or alternatives to prefer.

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