Katzilla MCP

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

The description adds valuable behavioral context beyond annotations: it discloses the data source (Open Library API with CC0 1.0 license), update frequency ('updates daily'), and output format details (Katzilla envelope with quality scores and citation info). Annotations cover read-only, non-destructive, idempotent, and open-world hints, but the description enriches this with operational specifics like freshness and auditability, without contradicting 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 description is front-loaded with the core purpose in the first sentence, followed by essential behavioral details in subsequent sentences. Every sentence adds critical information (e.g., data source, output format), with zero waste or redundancy, making it highly efficient 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?

Given the tool's moderate complexity, rich annotations (read-only, idempotent, etc.), and the presence of an output schema, the description is complete. It covers purpose, usage context, behavioral traits (source, updates, output format), and aligns with structured data, leaving no significant gaps for an AI agent to understand and invoke the tool correctly.

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 description mentions search by 'title, author, or keyword,' which aligns with the 'query' parameter in the schema, but adds no additional semantic details beyond what the schema provides (e.g., no examples or advanced usage). With 100% schema description coverage, the baseline is 3, as the schema fully documents parameters, and the description offers minimal extra value here.

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 explicitly states the tool's purpose: 'Search for books by title, author, or keyword using the Open Library API.' It specifies the verb ('Search'), resource ('books'), and scope ('by title, author, or keyword'), and distinguishes it from sibling tools by mentioning the specific API (Open Library), which none of the other tools use for book searches.

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 provides clear context for when to use the tool: for searching books via the Open Library API. It does not explicitly state when not to use it or name alternatives, but the specificity of the API and data source (Open Library) implies it's the primary tool for this purpose among siblings, which include general search tools like 'culture__open-library' but not identical book-search functions.

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