Katzilla MCP

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

Annotations already indicate read-only, non-destructive, idempotent, and open-world behavior, but the description adds valuable context beyond this: it specifies the data source, update frequency (daily), and details about the return structure (quality scores, citation with URL, license, and SHA-256 hash), which helps the agent understand freshness, auditability, and output format.

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, followed by source details and return format, all in three concise sentences with no wasted words. Every sentence adds essential information, making it efficient and well-structured for quick comprehension.

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 (implied by 'Returns the Katzilla envelope'), the description is complete enough. It covers purpose, source, update frequency, and return structure, leaving detailed output to the schema, which aligns with best practices.

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 description coverage is 100%, so the schema fully documents the 'keyword' and 'limit' parameters. The description does not add any parameter-specific semantics beyond what the schema provides, such as examples of keyword usage or implications of the limit, but it meets the baseline for high schema coverage.

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's purpose with specific verbs ('Search National Science Foundation research grants') and resources ('titles, abstracts, funding amounts, awardees, and program names'), and distinguishes it from siblings by specifying its unique domain (NSF awards) and data source, unlike other science tools like arXiv or PubMed.

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 usage by mentioning the data source (National Science Foundation), update frequency (daily), and return format (Katzilla envelope), but does not explicitly state when not to use it or name alternatives among siblings, such as science__nih-reporter or science__openalex for other research databases.

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