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

Annotations already declare this as read-only, idempotent, and non-destructive. The description adds meaningful behavioral context by explaining that each book was recommended by at least two independent sources and ranked by mention count, which sets expectations about the list construction and ranking methodology.

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 three sentences: purpose, methodology, usage context, and parameter clarification. It is front-loaded, non-redundant, and contains no filler, making it highly concise and well-structured.

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 two-parameter retrieval tool with a full output schema, the description covers purpose, methodology, usage guidance, and input format. Nothing critical is missing given the annotations and schema already provide safety and return-type context.

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 input schema already documents both parameters with examples and 100% coverage. The description reinforces the 'topic or slug' input format but adds little new meaning beyond what the schema provides, so the baseline of 3 is appropriate.

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 states the tool returns one of MRB's 1,300+ consensus 'best books' lists for a topic, using a specific verb and resource. It distinguishes from sibling tools by emphasizing 'consensus' and 'multiple experts,' which is unique compared to person-specific or search tools.

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 explicitly provides a use case: 'when a user asks for "the best X books" and you want a ranking backed by multiple experts rather than one opinion.' It gives clear context but does not name alternatives or provide when-not-to-use conditions, so it stops short of a 5.

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