Katzilla MCP

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

The description adds valuable behavioral context beyond annotations: it specifies the data source ('NASA FIRMS'), update frequency ('real-time'), and output structure ('Returns the Katzilla envelope { data, quality, citation }'). Annotations already indicate it's read-only, non-destructive, idempotent, and open-world, but the description enhances this with details on data freshness, quality scoring, and audit features like the SHA-256 hash, which are not covered by 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 highly concise and well-structured: it starts with the core purpose, adds source and update details, and concludes with the return format—all in two sentences with no redundant information. Every sentence adds value, such as clarifying the output envelope and its components, making it efficient and easy to parse.

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 (real-time satellite data retrieval), rich annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint), and the presence of an output schema, the description is complete. It covers the purpose, source, update behavior, and output structure, compensating for any gaps. With annotations and output schema handling safety and return values, the description provides sufficient context for effective use.

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 each parameter (west, south, east, north, days) clearly documented in the schema. The description does not add any parameter-specific semantics beyond what the schema provides, such as explaining how the bounding box works or the implications of the 'days' parameter on data retrieval. This meets the baseline score of 3 since the schema handles parameter documentation adequately.

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 active fire/hotspot data from NASA FIRMS (Fire Information for Resource Management System) using VIIRS satellite imagery.' It specifies the verb ('Get'), resource ('active fire/hotspot data'), source ('NASA FIRMS'), and methodology ('VIIRS satellite imagery'), distinguishing it from sibling tools like 'hazards__fema-disasters' or 'hazards__usgs-earthquakes' which cover different hazard types.

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: it's for real-time wildfire data from a specific NASA system, implying it's suitable for environmental monitoring or disaster response. However, it does not explicitly state when not to use it or name alternative tools for similar data, such as other hazard-related siblings like 'environment__copernicus' or 'hazards__hurricane-tracking', which could help differentiate further.

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