Katzilla MCP

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds valuable context beyond annotations: it specifies the data source, update frequency ('updates daily'), and details the return format ('Katzilla envelope { data, quality, citation }') with quality metrics and citation information. This enhances 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 well-structured and concise, with two sentences that efficiently convey purpose, data details, and return format. Every sentence adds value: the first explains what the tool does and the data structure, and the second covers source, updates, and output envelope. There is no wasted text, and key information is front-loaded.

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 (simple read-only query), rich annotations (covering safety and behavior), and the presence of an output schema (implied by 'Returns the Katzilla envelope'), the description is complete. It explains the tool's function, data source, update frequency, and output structure, leaving no significant gaps for an AI agent to understand and use the tool effectively.

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 the 'limit' parameter fully documented in the schema. The description does not add any parameter-specific information beyond what the schema provides, such as default usage or examples. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't need to.

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: 'Current travel advisories from the U.S. Department of State. Returns advisory level (1-4), country, and description.' It specifies the verb ('returns'), resource ('travel advisories'), and distinguishes itself from siblings by focusing on government travel data rather than agriculture, consumer, or other domains. The explanation of advisory levels adds specificity.

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 implies usage context by mentioning the data source and update frequency ('Source: U.S. Department of State (Public Domain), updates daily'), but it does not explicitly state when to use this tool versus alternatives or any prerequisites. Among siblings, it's clear this is for government travel data, but no direct comparisons or exclusions are provided.

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