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 of behavioral disclosure. It describes a read-only operation ('Get solar energy resource data') but does not mention any behavioral traits such as rate limits, authentication requirements, data freshness, error conditions, or response format. For a tool with zero annotation coverage, this is a significant gap in transparency.

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 appropriately sized and front-loaded, consisting of two concise sentences that directly state the tool's function and practical use. Every sentence earns its place by providing essential information without redundancy or unnecessary detail.

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 moderate complexity (geospatial data retrieval), lack of annotations, and no output schema, the description is incomplete. It adequately covers the purpose and scope but fails to address behavioral aspects (e.g., rate limits, data sources) and output details (e.g., data structure, units). The description compensates partially but not fully for the missing structured information.

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 (lat and lon are clearly documented), so the baseline score is 3. The description adds no additional parameter semantics beyond what the schema provides—it does not explain coordinate formats, valid ranges, or precision requirements. It only implies that parameters define the location for solar data.

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 solar energy resource data') and resources ('any U.S. location'), and distinguishes it from sibling tools by focusing on solar irradiance data rather than other economic, health, or government datasets listed. It explicitly mentions the output format ('monthly and annual solar irradiance') and practical application ('Shows potential for solar panels').

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 by specifying 'any U.S. location' and the type of data returned, but does not explicitly state when to use this tool versus alternatives (e.g., other NREL tools like nrel_fuel_stations or nrel_utility_rates). It provides basic scope but lacks guidance on prerequisites, exclusions, or comparisons to sibling tools.

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