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. While 'List' implies a read-only operation, the description doesn't specify whether this tool requires authentication, has rate limits, returns paginated results, or what the output format looks like (e.g., list of strings, JSON objects). It mentions dataset types but doesn't explain behavioral aspects like response time or error conditions.

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 a single, efficient sentence that front-loads the core purpose ('List available NOAA climate datasets') and provides helpful examples in parentheses. There is no wasted verbiage or redundant information, making it appropriately sized for a simple listing tool.

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 (0 parameters, no annotations, no output schema), the description is minimally adequate. It states what the tool does and gives examples, but lacks details on output format, behavioral constraints, or usage context. For a listing tool with no structured metadata, more completeness would be beneficial (e.g., explaining what 'available' means or how results are structured).

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 tool has 0 parameters, and schema description coverage is 100% (since there are no parameters to describe). The description doesn't need to add parameter semantics beyond what the schema already provides (which is nothing). The baseline for 0 parameters is 4, as there's no parameter information to compensate for or enhance.

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: 'List available NOAA climate datasets' with specific examples (GHCND daily, GSOM monthly, GSOY annual, normals, etc.). This is a specific verb ('List') + resource ('NOAA climate datasets') combination. However, it doesn't explicitly distinguish itself from potential sibling tools like 'noaa_climate_data' or 'list_datasets' that might exist in the same context, though those appear to be different tools in the sibling list.

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 alternatives. It doesn't mention any prerequisites, constraints, or relationships with other tools (e.g., whether this should be used before fetching data with 'noaa_climate_data'). The user must infer usage from the tool name and description alone.

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