get_reviews

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

No annotations provided, so description carries full burden. Discloses review order ('most relevant'), aggregation across editions, limit cap at 100, and server-side filtering. Lists each field returned (reviewer name, rating, text, etc.), making behavior fully transparent.

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?

Concise yet informative: opening sentence states purpose, followed by paragraph on behavior and returned data, then parameter explanations. No wasted words, well-organized.

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?

Covers tool purpose, data source, return fields, parameter effects, constraints. With 5 parameters and an output schema, the description provides sufficient context for correct invocation.

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 has 0% description coverage. Description adds meaning for each parameter: limit (capped at 100, true pagination), min_rating/max_rating (server-side star filters), exclude_spoilers (drops flagged spoilers). book_id is implicitly clear. Adds substantial value beyond schema.

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?

Clearly states the tool gets reader reviews for a book, emphasizing actual text versus score. Distinguishes from siblings like 'get_book' or 'get_shelf' by focusing on reviews.

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?

Provides context on data source (Goodreads GraphQL), pagination, ordering, and aggregation across editions. Implicitly indicates when to use (getting reviews) but lacks explicit 'when not to use' or comparison with siblings.

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