census_query

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

Annotations already declare readOnlyHint=true, which the description does not contradict. The description adds helpful examples of datasets and variables but does not disclose other behavioral traits like response format, pagination, or potential errors. Bar is lowered by annotations, but still room for more context.

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 and provides practical examples in a structured list. It is concise enough without being too terse, though the examples could be integrated more tightly.

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?

The tool has no output schema and 4 parameters, making it moderately complex. The description covers input examples but omits details about the return format (e.g., JSON, CSV) or error handling, which would help agents understand the full behavior.

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?

Input schema provides 100% coverage with descriptions for all parameters. The description adds value by including concrete examples for dataset, variables, and for_geo, which enriches the semantic understanding beyond the schema alone.

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 queries the U.S. Census Bureau Data API and lists supported datasets. It distinguishes from sibling tools like census_population and census_search_variables by being the general-purpose query tool, but does not explicitly differentiate.

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 examples of common datasets and variables, implying usage context. However, it does not explicitly state when to use this tool versus siblings like census_population or census_search_variables, nor does it offer any exclusions or prerequisites.

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