Katzilla MCP

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

The annotations already indicate read-only, non-destructive, idempotent, and open-world behavior, covering safety and reliability. The description adds valuable context beyond this by disclosing the source ('Hebcal (Free API)'), update frequency ('updates monthly'), and the return format ('Katzilla envelope with quality scores and citation details'), enhancing transparency 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 details about the source, updates, and return format in a compact manner. Every sentence contributes necessary information without redundancy, making it efficiently structured and easy to parse.

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 low complexity (2 optional parameters, 100% schema coverage, annotations covering key behavioral traits, and an output schema implied by the return format description), the description is complete. It adequately explains the tool's function, source, update cadence, and output structure, leaving no significant gaps for an AI agent to understand and invoke it 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 input schema has 100% description coverage, with clear documentation for 'year' and 'month' parameters. The description does not add any additional meaning or syntax details beyond what the schema provides, such as how these parameters affect the output. Thus, it meets the baseline for high schema coverage without compensating further.

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 with a specific verb ('Get') and resource ('Jewish calendar events and holidays from Hebcal'), clearly distinguishing it from sibling tools that cover diverse domains like agriculture, consumer data, or entertainment. It directly addresses what the tool does without ambiguity.

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 this tool by specifying the data source ('Hebcal (Free API)') and update frequency ('updates monthly'), which helps in decision-making. However, it does not explicitly state when not to use it or name alternatives among sibling tools, which are all in different categories, so differentiation is implied but not direct.

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