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

The annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context by clarifying that counts are catalog facts, NOT pull-rate probabilities, which helps prevent misinterpretation of the output. It also specifies that counts refer to card faces and variant splits, adding meaning beyond the annotations.

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 main English description is concise and front-loaded with the core purpose, followed by a practical answer-oriented sentence and a useful caveat. However, the Chinese sentence nearly duplicates the English content, adding redundancy and token cost without introducing new information.

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?

Given the simple two-parameter schema, an output schema, and annotations covering safety, the description is complete enough for correct invocation. It covers what the tool returns conceptually, the intended use case, and an important interpretative caveat, leaving no critical gap for the agent.

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 set_code and lang are already documented in the input schema. The description does not add parameter-specific details, but it does not need to; the baseline of 3 applies because the schema carries the semantic weight.

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: a per-Pokémon breakdown for one set, covering card-face counts and variant splits. It also states the question the tool answers, 'which Pokémon has the most versions in this set'. It does not explicitly name or differentiate sibling tools, so it stops short of a 5.

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 gives a clear use case: when you need variant counts per Pokémon in a set, or want to answer 'which Pokémon has the most versions in this set'. It does not explicitly describe when not to use it or point to alternatives, but the context is strong enough for an agent to select it appropriately.

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