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

Annotations already declare read-only, idempotent, non-destructive, closed-world behavior, so the bar is lower. The description still adds useful context annotations cannot express: results are limited to 'verified' recommenders and each carries a quote and original-source link. It does not cover no-match or ambiguity behavior.

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?

Three sentences, front-loaded with what the tool returns, then when to use it, then input form. The one weak spot is 'This is MRB's signature dataset', which is promotional rather than operational.

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?

An output schema exists, so return-value detail is already covered, and the description still summarizes the payload adequately. Remaining gaps are minor edge-case behavior (book not found, multiple title matches) for an otherwise simple single-parameter read tool.

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 coverage is 100% with a single documented parameter, so the baseline would be 3. The description goes beyond the schema by stating the input may be a bare title OR author+title for disambiguation, which is non-obvious given the schema only exposes one free-text 'title' field.

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 ('Return every verified person who recommends a given book') plus the payload shape (quote + source link). This implicitly distinguishes it from the inverse-direction sibling get_person_recommendations, though no sibling is named explicitly.

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?

Gives concrete triggering phrasings ('who recommends Sapiens?', 'is Zero to One worth reading?', social proof/expert opinions) so the agent can pattern-match user intent. It stops short of naming when to prefer get_person_recommendations or get_summary instead, so exclusions and alternatives are left to inference.

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