US Economic Data

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

Annotations already provide readOnlyHint, idempotentHint, and openWorldHint. The description adds context beyond annotations by naming the data source (ACS 5-year estimates) and implying that data is aggregated over a period, which is valuable for understanding currency and statistical nature.

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?

Two sentences, no fluff. The first sentence captures the action and scope; the second adds source and use cases. Every sentence adds value, and the structure is optimal for quick comprehension.

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 description covers purpose, data source, and high-level use cases. With an output schema present (context signals), return value explanation is unnecessary. However, it could mention data vintage or query limits, but overall it is sufficient for an agent to understand the tool's role.

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 coverage is 100%, so baseline is 3. The description does not add meaning to the parameters beyond what the schema already provides (e.g., state_fips, county_fips, year). It lists output indicators but not parameter details, so it stays at baseline.

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 starts with a specific verb ('Get'), identifies the resource ('economic indicators for any US geography'), and lists concrete indicators (median household income, population in poverty, unemployed count). It also implicitly distinguishes from sibling tools like census.data.demographics and census.data.housing by focusing on economic metrics.

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 includes use cases (market sizing, real estate analysis, business location intelligence) that imply when to use, but it does not explicitly contrast with sibling tools or state when not to use. There is no direct 'use this for X, not for Y' guidance, which weakens the score.

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