get_reader_recommendations

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

No annotations are supplied, so the description carries the full disclosure burden. It only restates the read operation ('조회합니다') and adds no information about output shape, pagination, authentication, or edge cases; the behavior beyond the tool name is effectively undisclosed.

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 short sentence with no filler and is easy to parse. It is appropriately concise, though the brevity comes at the cost of substantive behavioral and usage detail.

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 tool with full schema coverage, the essential invocation data is present. However, with no annotations, no output schema, and no mention of when to choose this over get_mania_recommendations, the description is only minimally viable rather than fully complete.

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 the single isbn13 parameter with 100% coverage, including format and semicolon-separated multi-value behavior. The description adds no parameter-level detail, so it neither enhances nor detracts from the schema; 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?

The description uses a clear verb ('조회합니다') and a specific resource ('다독자 추천도서'), so an agent can understand it returns recommended books for avid readers. However, it does not explicitly differentiate itself from the similar sibling get_mania_recommendations, leaving that distinction to the tool name.

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 '다독자 추천도서를 조회합니다' implies a use case: when a request concerns recommendations for heavy readers. It provides no explicit when-to-use guidance, exclusions, or alternatives, so the agent must infer selection criteria from the Korean term alone.

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