chilean_households

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. However, the description adds no behavioral context beyond that. It does not state what the tool returns, whether it generates synthetic data, whether it accepts inputs like data_path, or any other runtime behavior. The minimal one-liner leaves the agent guessing about the actual 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 very concise (one short sentence), which is good for brevity but not for effectiveness. It lacks a verb or any structural guidance, making it more under-specified than efficiently front-loaded. It does not earn its place as a complete guide.

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?

Despite having an output schema and complete parameter descriptions, the tool description is too sparse. It does not explain what kind of data is produced, how it should be used, or why it differs from other dataset tools. An agent would need to open the schema or call the tool to understand its purpose, which is a significant gap for a tool with 8 parameters and a rich output schema.

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 input schema already documents all 8 parameters. The description adds no parameter-specific meaning, but the baseline of 3 applies because the schema handles 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 'Chilean-style household income with urban/rural gap' is a noun phrase that identifies the subject but lacks an explicit verb. It vaguely suggests this tool provides or generates household income data, but does not clearly state an action like 'generate', 'load', or 'return'. It adds a distinguishing feature (urban/rural gap) but does not clearly differentiate from sibling dataset tools like 'cps_wage' or 'basque_terrorism'.

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?

There is no guidance on when to use this tool versus alternatives. The description does not mention comparisons, alternatives, or conditions for use. An agent browsing the large sibling list would not know why to pick chilean_households over other dataset tools.

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