US Government Open Data MCP

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns a forecast (not real-time data) and includes a UV scale for interpretation, which adds useful behavioral context. However, it lacks details on rate limits, error handling, authentication needs, or response format, leaving gaps for a mutation-free query tool.

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 three sentences: the core function, the UV scale for interpretation, and the usage context. Each sentence adds distinct value without redundancy, making it front-loaded 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 low complexity (simple query with no output schema and no annotations), the description is largely complete. It covers purpose, usage context, and output interpretation (UV scale). However, it lacks details on the forecast timeframe (e.g., daily, hourly) or response structure, which could enhance completeness for an agent.

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 three parameters (zip, city, state) with their constraints. The description adds no parameter-specific information beyond what the schema provides, such as examples or additional usage notes, meeting the baseline for high schema coverage.

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 specific action ('Get UV index forecast') and resource ('for a U.S. location'), distinguishing it from all sibling tools which are unrelated to UV index or EPA data. It provides the exact scope (forecast) and geographic limitation (U.S.), making the purpose unambiguous.

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 explicitly states when to use this tool ('for health recommendations -- high UV correlates with skin cancer risk'), providing clear context for its application. However, it does not mention when not to use it or name any alternatives among sibling tools, 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.