US Government Open Data MCP

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

Annotations already declare readOnlyHint=true, indicating a safe read operation. The description adds useful context by specifying the datasets available and mentioning SODA syntax, but doesn't disclose behavioral traits like rate limits, authentication needs, or query result formats. 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 a concise dataset list. It avoids redundancy, though the dataset enumeration is lengthy but necessary for clarity. Every sentence contributes to understanding the tool's scope.

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 complexity (6 parameters, no output schema) and rich annotations (readOnlyHint), the description is reasonably complete. It covers datasets and syntax, but could improve by mentioning result formats or error handling. The high schema coverage mitigates gaps.

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 each parameter well-documented (e.g., 'dataset_id' as Dataset ID, 'where' as SODA clause). The description adds value by listing example dataset IDs (e.g., 'bi63-dtpu') and reinforcing SODA usage, but doesn't provide additional syntax or format details beyond the schema.

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 ('Custom query'), target resource ('any CDC dataset'), and method ('using SODA syntax'), with a comprehensive list of available datasets. It distinguishes itself from sibling tools like 'cdc_causes_of_death' or 'cdc_covid' by offering flexible querying across multiple datasets rather than fixed endpoints.

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 implicitly guides usage by listing specific CDC datasets (e.g., 'bi63-dtpu' for death data) and referencing SODA syntax, suggesting it's for custom data exploration. However, it lacks explicit guidance on when to use this versus simpler sibling tools (e.g., 'cdc_covid' for direct COVID data) or alternatives like 'census_query'.

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