query_census

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'raw query' and 'raw JSON response', which implies direct API interaction, but doesn't disclose important behavioral traits like rate limits, authentication requirements, error handling, or whether this is a read-only operation. The description provides minimal behavioral context beyond the basic operation.

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 perfectly structured and front-loaded with the core purpose, followed by organized parameter documentation and return value clarification. Every sentence earns its place, with no wasted words. The Args/Returns formatting makes it easy to scan while maintaining complete information density.

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?

For a 4-parameter tool with no annotations and no output schema, the description provides adequate parameter documentation but lacks important contextual information. It doesn't explain the nature of the 'raw JSON response' structure, doesn't mention rate limits or authentication, and provides no guidance on error scenarios. While the parameter coverage is excellent, other contextual gaps remain.

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?

With 0% schema description coverage, the description fully compensates by providing clear semantic explanations for all 4 parameters. Each parameter gets specific examples and context: dataset paths like 'acs/acs5', variable codes as a list, geography specifications with examples, and year with default value. This adds substantial meaning beyond the bare 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 ('Make a raw query') and target resource ('Census API'), distinguishing it from sibling tools that query different data sources like NASA, NOAA, or WorldBank. It provides a precise verb+resource combination that leaves no ambiguity about what this tool does.

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 no guidance on when to use this tool versus alternatives. While it's clear this is for Census data, there's no mention of when to choose it over other demographic tools like 'get_demographics' or 'get_population', nor does it specify prerequisites or constraints for effective use.

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