Census ACS Demographics

get_county_education

Get educational attainment for counties (population 25+).

Returns counts and percentages for: less than high school, high school diploma/GED,
some college/associate degree, bachelor's degree, and graduate/professional degree.

Args:
    state: Two-letter state abbreviation (e.g. 'WA', 'CA') or 2-digit FIPS code.
    county_fips: Three-digit county FIPS code (e.g. '033' for King County).
                 Omit to get all counties in the state.
    year: ACS 5-year estimate year (default 2022).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`year`	No
`state`	Yes
`county_fips`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains what is returned (counts and percentages for five categories) and notes that the data source is ACS 5-year estimates. It also clarifies the county_fips omission behavior. More detail on edge cases (e.g., invalid FIPS) is missing, but the core behavior is well communicated.

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?

The description is well-structured and concise. It opens with a clear one-line summary, then lists the returned metrics, and follows with a compact 'Args' section. Every sentence adds value with no fluff or redundancy.

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?

The description is complete for a read-only data retrieval tool given the presence of an output schema and explanation of all parameters. It covers the data source (ACS 5-year), the geographic level (counties), and the omission behavior. Slight gaps remain around handling of missing data or output formatting, but these are partially addressed by the output schema.

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

Parameters5/5

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

The schema provides no descriptions (coverage 0%), so the description is essential. It fully defines each parameter: state accepts either two-letter abbreviation or 2-digit FIPS, county_fips is a three-digit code with a note that omission returns all counties, and year specifies ACS 5-year estimate with a default of 2022. 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.

Purpose5/5

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

The description clearly states the tool retrieves educational attainment for counties, with a specific verb ('Get'), resource ('counties'), and subject ('educational attainment'). It also lists five distinct categories of attainment, which differentiates it from sibling tools like get_county_demographics or get_commuting_data.

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

Usage Guidelines3/5

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

The description provides usage details for parameters (state, county_fips, year) including how to omit county_fips for all counties, but does not explicitly compare with sibling tools or state when to use this tool instead of alternatives. The guidance is present for parameter handling but not for tool selection.

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

All Census ACS Demographics tools Inspect

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TDQS

A4.4/5.0

Disambiguation5/5

Each tool targets a distinct subject area (commuting, demographics, economics, education) or geographic level (tract). No two tools overlap in purpose, making selection unambiguous.

Naming Consistency4/5

All tools start with 'get_' and mostly follow a 'get_county_<topic>' pattern, but 'get_commuting_data' and 'get_tract_data' deviate slightly from the fully consistent pattern. Still, the convention is predictable and readable.

Tool Count5/5

Five tools is well-scoped for a Census ACS demographics server. Each thematic area and geographic level earns its place without unnecessary bloat or redundancy.

Completeness4/5

The four county-level tools cover key demographic, economic, education, and commuting themes, and the flexible tract-level tool can query any ACS variable, covering niche needs. A minor gap is the lack of a dedicated county-level variable query, but the tract tool compensates.

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