Dict Metro

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

No annotations are supplied, so the description carries the full burden; it does disclose the return shape (grouped by city, with station ids) and implicitly that the result set is bounded to cities having a metro map. It says nothing about auth requirements, result size, or whether the response is static reference data, which for a no-param dictionary tool is a modest but real gap.

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?

A single sentence with zero filler, and the grouping/station-id detail that matters most for downstream use is placed at the end where it is easy to scan. Nothing is redundant.

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?

There is no output schema, so the description must characterize the return value; it does so at a high level (per-city grouping, station ids). It would be stronger if it named the line-level fields (e.g. line id/name) that a caller must traverse to reach the stations.

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 tool takes zero parameters, so there is nothing to document and the baseline is 4. The description correctly signals that no input is needed by framing the call as a global fetch.

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?

States a specific verb and resource ("Get metro lines and stations") and scopes it to "all hh.ru cities that have a metro map," which implicitly distinguishes it from the sibling dict_metro_city (single city). The sibling is never named, so the differentiation requires inference rather than being explicit.

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 phrase "for all hh.ru cities" implies this is the bulk/all-cities variant, but the description never says when to prefer it over dict_metro_city or dict_areas. No prerequisites, no exclusions, no alternative named.

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