Census County Business Patterns

compare_county_industries

Get a breakdown of all industries in a county.

Returns business pattern data for all 2-digit NAICS sectors in a
specific county. Useful for understanding the economic composition
of a community for grant narratives.

Args:
    state: Two-letter state abbreviation (e.g. 'CA', 'TX', 'NY').
    county_fips: 3-digit county FIPS code (e.g. '037' for Los Angeles County).
    year: Data year (default 2021). Available: 2012-2021.

Input Schema

TableJSON Schema

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

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A3.9/5.0

Behavior3/5

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

No annotations provided, so description carries full burden. It discloses that data covers all 2-digit NAICS sectors and includes year range, but does not mention rate limits, auth requirements, or pagination. Adequate but not exhaustive.

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?

Description is concise (4 lines plus Args section), front-loaded with purpose, and structured in a clear 'what it does, what it returns, when to use' flow. The Args section is well-organized and adds value without 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?

Output schema exists, so no need to document return values. Description covers purpose, usage context, and parameters thoroughly. Lacks mention of edge cases (e.g., large county performance) but sufficient for typical use.

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 description coverage is 0%, so description fully compensates. It clearly documents state format (two-letter abbreviation), county_fips format (3-digit code with example '037'), and year (default 2021, range 2012-2021). Every parameter is explained with concrete details.

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

Purpose4/5

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

Description clearly states 'Get a breakdown of all industries in a county' and specifies returns business pattern data for all 2-digit NAICS sectors. It explains the purpose for grant narratives but does not explicitly differentiate from sibling tools like get_county_business_patterns or get_state_business_summary.

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 implies usage for understanding economic composition and grant narratives, but does not provide explicit when-to-use or when-not-to-use guidance, nor contrasts with sibling tools.

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

All Census County Business Patterns tools Inspect

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TDQS

A4.3/5.0

Disambiguation5/5

Each tool targets a distinct granularity: compare_county_industries focuses on a breakdown of all industries in a single county, get_county_business_patterns provides county-level data with optional industry filters (including totals for all industries), and get_state_business_summary offers state-level aggregates. Descriptions clearly differentiate their use cases.

Naming Consistency4/5

All tool names use a verb_noun pattern (compare_county_industries, get_county_business_patterns, get_state_business_summary). The only minor inconsistency is the use of 'compare' vs. 'get', but the pattern is otherwise uniform and readable.

Tool Count5/5

With only 3 tools, the set is focused and well-scoped for the Census County Business Patterns domain. Each tool provides essential functionality (state-level, county-level with filtering, and full industry breakdown), and no tool seems redundant or unnecessary.

Completeness5/5

The tools cover the core operations needed for business patterns data: state summary, county-level data with optional industry filtering, and a comprehensive industry breakdown for a county. The ability to retrieve all counties in a state via get_county_business_patterns adds flexibility, and the year parameter allows time-series access. No obvious gaps for the stated purpose of grant narratives.

Resources

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