Census ACS Demographics

get_commuting_data

Get means of transportation to work data for counties.

Returns worker counts and percentages for: drove alone, carpooled,
public transit, walked, bicycle, taxi/motorcycle/other, and worked from home.

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

A4.6/5.0

Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses that the tool returns worker counts and percentages for seven transportation categories, and specifies that omitting county_fips returns all counties in the state. It does not mention potential limitations or error handling, but for a read-only data retrieval tool, this level of transparency is adequate.

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 compact and well-organized with an introductory sentence, a list of returned categories, and a clear Args section. No unnecessary words, and each sentence serves a purpose.

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

Completeness5/5

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

The tool has moderate complexity with 3 parameters and no annotations. The description covers purpose, parameter semantics, and return values sufficiently. An output schema exists, so return format details are not required in the description.

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?

Schema coverage is 0%, so the description fully compensates by explaining the format and behavior of each parameter: state accepts abbreviation or 2-digit FIPS, county_fips is optional with a specific 3-digit format and scope, year defaults to 2022 and refers to ACS 5-year estimates. This adds significant meaning beyond the 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 uses a specific verb 'Get' with a clear resource: 'means of transportation to work data for counties.' It explicitly lists the data categories returned (drove alone, carpooled, public transit, etc.), which clearly differentiates it from sibling tools focused on demographics, economics, education, or tract-level data.

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 gives clear context for when to use this tool (when commuting data is needed) and explains parameter usage (state, county_fips, year). It does not explicitly name alternatives or state when not to use it, but the purpose is distinct enough that the intended usage is unambiguous.

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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