ltmv

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

With no annotations, the description carries the full burden. It thoroughly explains the request format, parameters, and response structure for both JSON and CSV. It is clear this is a read-only data retrieval operation, and no destructive or complex behavior is implied.

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 well-structured with clear sections for parameters, request example, and response keys. It is not overly verbose for the amount of information conveyed, but could be slightly more streamlined.

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 simplicity (2 optional parameters, no output schema), the description covers all necessary aspects: purpose, parameters with examples, and comprehensive response keys for both formats. No output schema exists, but the description compensates by detailing return values.

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 already fully describes both parameters (lang, rformat) with their defaults and options. The description restates this information and adds a request example, but adds no deeper semantic meaning or constraints beyond what the schema provides.

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 'Latest 10-minute Mean Visibility (LTMV) API Request' and details what the tool returns: visibility data from automatic weather stations. It clearly distinguishes from sibling tools which cover other weather parameters like rainfall, temperature, and warnings.

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 no guidance on when to use this tool versus the many sibling tools. It does not mention any context, prerequisites, or alternative tools for similar data. The agent is left to infer usage alone.

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