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 context about the data source ('CDC'), time range ('1999–2017'), and example causes, which supplements annotations. However, it doesn't disclose behavioral traits like rate limits, pagination (implied by 'limit' parameter), or error handling. 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 front-loaded with the core purpose in the first sentence, followed by supporting details in the second. Both sentences are essential: the first defines the tool's function, and the second provides data context. There is zero waste or redundancy, making it highly efficient.

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), the description is reasonably complete. It covers purpose, data range, and examples, but lacks details on output format or error cases. With annotations indicating read-only and schema fully describing parameters, the description provides adequate context, though not exhaustive.

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 parameter descriptions in the schema (e.g., 'Full state name', 'Year (1999–2017)', 'Max records (default 200)'). The description adds no parameter-specific semantics beyond what's in the schema, such as format details or constraints. With high schema coverage, the baseline score of 3 is appropriate.

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 leading causes of death in the U.S. by state and year.' This specifies the verb ('Get'), resource ('leading causes of death'), and scope ('U.S., state, year'). It distinguishes from siblings like 'cdc_death_rates_historical' or 'cdc_mortality_rates' by focusing on causes rather than rates, but doesn't explicitly differentiate them.

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 through the data range ('1999–2017') and example causes, but provides no explicit guidance on when to use this tool versus alternatives like 'cdc_death_rates_historical' or 'cdc_mortality_rates'. It mentions 'Causes include heart disease, cancer, kidney disease, etc.' which hints at content, but lacks clear when/when-not instructions or named alternatives.

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