Katzilla MCP

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

Annotations already indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds valuable behavioral context beyond this by specifying the return format ('Katzilla envelope { data, quality, citation }') and explaining quality scores ('freshness/uptime/confidence') and citation details ('source URL, license, SHA-256 data hash'), which helps the agent understand output structure and data integrity.

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 highly concise and well-structured, with two sentences that efficiently convey purpose, source, update frequency, and return format without any wasted words. It is front-loaded with the core function and follows with detailed output explanation.

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 covering safety and idempotency, and an output schema (implied by 'Has output schema: true'), the description is complete. It adds necessary context about the data source, real-time updates, and detailed return format, compensating for any gaps and ensuring the agent can use it 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 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on output semantics, explaining the return structure and components like quality and citation. This adds meaningful context beyond the schema, though it's not directly about input parameters.

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 ('Get available weather radar map timestamps') and identifies the resource ('from RainViewer'). It distinguishes itself from sibling tools by specifying it's for international weather radar data, unlike other tools focused on agriculture, consumer data, etc., making its scope explicit.

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 by mentioning the source ('RainViewer (Free API)') and that it updates 'real-time', implying it's for current weather radar data. However, it does not explicitly state when not to use it or name alternatives, which prevents a perfect score.

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