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, covering safety and idempotency. The description adds valuable context beyond annotations: it specifies the data source (National Weather Service, Public Domain), update frequency (real-time), and return format (Katzilla envelope with quality scores and citation details), which helps the agent understand data freshness and auditability.

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 filtering options, source details, and return format in two efficient sentences. Every sentence adds value without redundancy, making it easy for an agent to parse 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 complexity (4 parameters, 100% schema coverage, annotations, and an output schema), the description is complete. It covers purpose, usage context, behavioral traits (source, updates, return format), and does not need to explain return values since an output schema exists. No gaps are present for effective tool selection and invocation.

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 all parameters (area, severity, urgency, limit). The description mentions filtering by state, severity, and urgency, which aligns with the schema but does not add significant semantic details beyond what the schema provides, such as explaining parameter interactions or default behaviors.

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 action ('Get active weather alerts') and resource ('from the National Weather Service'), and distinguishes itself from sibling tools by specifying its domain (hazards) and data source (NWS), unlike other tools in the list (e.g., hazards__fema-disasters, hazards__usgs-earthquakes).

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 ('Filter by state, severity, and urgency') and implies when to use it (for real-time weather alerts), but does not explicitly state when not to use it or name alternatives among sibling tools (e.g., hazards__fema-disasters for disaster data).

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