Katzilla MCP

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

The description adds valuable behavioral context beyond annotations: it specifies the data source (CMS NPPES), update frequency (daily), and details about the return format (Katzilla envelope with quality scores and citation including SHA-256 hash). Annotations already cover read-only, non-destructive, idempotent, and open-world hints, so the description appropriately supplements with practical usage information without contradicting them.

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 additional context in a second sentence, with no wasted words. Each sentence provides essential information (search functionality, data source, return format), making it efficient and well-structured for quick understanding.

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 complexity (search with multiple parameters), rich annotations (read-only, idempotent, etc.), and the presence of an output schema, the description is complete enough. It covers the purpose, data source, update frequency, and return format, which, combined with structured fields, provides a comprehensive understanding without needing to explain return values in detail.

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 parameters ('by NPI number, first name, or last name'), which aligns with the input schema properties. However, with 100% schema description coverage, the schema already fully documents all four parameters, so the description does not add significant semantic value beyond what is in the schema. 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 the CMS NPPES NPI Registry') and resources ('healthcare providers'), distinguishing it from sibling tools by specifying the exact data source (CMS NPPES NPI Registry) and search parameters (NPI number, first name, last name). It avoids tautology by providing operational details beyond the name/title.

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 ('Search... for healthcare providers by NPI number, first name, or last name') and mentions the data source and update frequency, which helps in decision-making. However, it does not explicitly state when not to use it or name alternative tools for similar purposes, such as other health-related sibling tools like 'health__cdc-data' or 'health__nih-clinical-trials'.

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