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 ('NOAA SWPC'), update frequency ('daily'), and return format details ('Katzilla envelope with quality scores and citation'), which helps the agent understand behavioral traits like 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 efficiently structured in two sentences: the first states the purpose and source, the second details the return format. Every sentence adds value without redundancy, and it is front-loaded with the core functionality.

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 has 0 parameters, rich annotations, and an output schema, the description is complete. It covers purpose, source, update frequency, and return format details, providing all necessary context for an agent to invoke the tool correctly without needing to rely solely on structured fields.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on output semantics, explaining the return structure ('Katzilla envelope { data, quality, citation }') and what 'quality' and 'citation' entail, adding meaningful context beyond the schema.

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: 'Get the latest planetary K-index (Kp) data from NOAA SWPC, indicating geomagnetic storm activity.' It specifies the verb ('Get'), resource ('K-index data'), source ('NOAA SWPC'), and distinguishes it from siblings by focusing on solar weather data, unlike other space tools like launch schedules or NASA images.

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 through '[Space & Astronomy Agent]' and mentions the data updates daily, but does not explicitly state when to use this tool versus alternatives (e.g., other space or environmental tools). It provides some implicit guidance but lacks explicit comparisons or exclusions.

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