US Government Open Data MCP

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

Annotations provide readOnlyHint=true, indicating a safe read operation. The description adds value by specifying the breakdown ('by major industry sector') and trend analysis ('growing or shrinking'), which aren't covered by annotations. However, it doesn't disclose behavioral details like rate limits, data freshness, or authentication needs. No contradiction with annotations exists.

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 front-loaded, consisting of two sentences that directly convey the tool's purpose and additional context. Every sentence adds value without redundancy, 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 moderate complexity (2 parameters, read-only operation), the description covers the core purpose and trend analysis. However, with no output schema, it lacks details on return format (e.g., structure of employment data). Annotations provide safety context, but the description could better address limitations or data sources for a more complete picture.

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%, with clear documentation for start_year and end_year parameters. The description doesn't add any parameter-specific details beyond what the schema provides, such as format constraints or examples. Baseline score of 3 is appropriate 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 employment numbers broken down by major industry sector' specifies the verb ('Get') and resource ('employment numbers'), and 'Shows which sectors are growing or shrinking' adds context about trend analysis. However, it doesn't explicitly differentiate from sibling tools like 'bls_series_data' or 'bls_cpi_breakdown' beyond the industry focus.

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?

No guidance is provided about when to use this tool versus alternatives. The description doesn't mention prerequisites, limitations, or comparisons to sibling tools like 'bls_series_data' for more granular data or 'bea_gdp_by_industry' for related economic metrics. Usage is implied through the description but not explicitly stated.

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