Katzilla MCP

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds valuable context beyond annotations by specifying the data source, update frequency ('updates daily'), and detailed return structure ('Katzilla envelope { data, quality, citation }') with explanations of quality scores and citation contents. No contradictions with annotations exist.

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 efficiently structured in two sentences: the first states purpose and scope, the second details return format and data characteristics. Every element serves a purpose with zero wasted words, making it easy to parse and understand quickly.

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, 100% schema coverage, and existence of an output schema, the description provides complete context. It explains what the tool does, data source, update frequency, and return structure in detail, compensating adequately where structured fields might not convey all necessary information for agent understanding.

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 already documents all four parameters thoroughly. The description adds marginal value by mentioning the entity types ('country, region, or ASN') and time range concepts, but doesn't provide additional syntax, format details, or constraints beyond what the schema provides. Baseline 3 is appropriate given complete 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 ('Query Internet Outage Detection and Analysis (IODA) for internet connectivity signals') and resources ('by country, region, or ASN'), distinguishing it from sibling tools which cover unrelated domains like agriculture, consumer, crypto, etc. It explicitly identifies the data source and type of analysis performed.

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 specifying the data source ('IODA (Georgia Tech)') and update frequency ('updates daily'), but provides no explicit guidance on when to use this tool versus alternatives or any prerequisites. It doesn't mention sibling tools or competing data sources for similar information.

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