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 describes the tool's purpose and output format, but lacks details on behavioral traits such as rate limits, authentication needs, error handling, or whether it's a read-only operation (implied by 'Get' but not stated). It adds some context about eligibility use but misses operational 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 efficiently structured in two sentences: the first covers the action, scope, and output details, and the second provides usage context. Every sentence adds value without redundancy, making it front-loaded and concise.

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 (3 parameters, no output schema, no annotations), the description is adequate but incomplete. It explains the purpose and usage context but lacks details on output format (e.g., structure of returned thresholds), error cases, or dependencies (like needing hud_list_counties for entity_id). Without annotations or output schema, more behavioral and operational context would be helpful.

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 the three parameters (state, entity_id, year). The description does not add any parameter-specific semantics beyond what the schema provides, such as explaining the relationship between state and entity_id or clarifying the fiscal year format. Baseline 3 is appropriate when the schema does the heavy lifting.

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'), resource ('HUD Income Limits'), and scope ('for a county, metro area, or entire state'), with explicit details about what data is returned ('Very Low, Extremely Low, and Low income thresholds by household size (1-8 persons)'). It effectively distinguishes this tool from its sibling tools (which are all from different agencies like BEA, BLS, CDC, etc.) by focusing on HUD housing data.

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 clear context for when to use this tool ('Used for affordable housing eligibility'), but it does not explicitly state when not to use it or name specific alternatives among the sibling tools. The input schema hints at an alternative (using 'hud_list_counties' to get entity_id), but the description itself lacks explicit guidance on tool selection.

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