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ACS Data Tool

acs_data_tool
Read-onlyIdempotent

Retrieve American Community Survey demographic and economic data, including population, income, employment, education, and housing statistics, for any U.S. geography and year.

Instructions

Retrieve demographic and economic data from the American Community Survey (ACS). Use this to get population statistics, household income, employment, education, housing data, and more. Supports both 1-year and 5-year estimates at various geographic levels.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYesYear for ACS data (e.g., 2022). Use the most recent year available.
datasetNoACS dataset: "acs1" (1-year estimates, more current but less detailed) or "acs5" (5-year estimates, more detailed and stable)acs5
variablesYesCensus variable codes to retrieve (e.g., ["B01001_001E", "B19013_001E"]). B01001_001E is total population, B19013_001E is median household income.
geographyNoGeographic level for data aggregationstate
stateNoState FIPS code (required for county, tract, place geographies)
countyNoCounty FIPS code (required for tract geography)
Behavior4/5

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

Annotations already declare readOnlyHint=true, etc., so the description doesn't need much. It adds that it supports 1-year and 5-year estimates, which is useful context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with purpose, no wasted words. Highly concise and effective.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 6 params, no output schema, the description covers the main purpose and options. Could mention return format but adequate for a data retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions. The description adds context about dataset and geography options, and example variable codes, providing additional meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it retrieves demographic and economic data from the ACS, listing specific data types and estimate types. This distinguishes it from siblings like decennial_census_tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says 'Use this to get...' which is clear, but it doesn't explicitly mention when not to use it or compare to alternatives, missing some guidance.

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

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