Census County Business Patterns

get_county_business_patterns

Get business establishment, employment, and payroll data by county.

Returns County Business Patterns data from the Census Bureau showing
the number of business establishments, employees, and annual payroll
for a given geography and optional industry filter.

Args:
    state: Two-letter state abbreviation (e.g. 'CA', 'TX', 'NY').
    county_fips: 3-digit county FIPS code (e.g. '037' for Los Angeles).
        If omitted, returns data for all counties in the state.
    naics_code: NAICS 2017 industry code to filter by (e.g. '72' for
        Accommodation/Food, '62' for Healthcare, '23' for Construction).
        If omitted, returns totals across all industries.
    year: Data year (default 2021). Available: 2012-2021.

Input Schema

TableJSON Schema

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

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.4/5.0

Behavior3/5

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

No annotations provided, so the description carries full burden. It mentions the data source (Census Bureau) and default behaviors for optional parameters. However, it does not discuss error conditions, data freshness, or any limitations beyond year range. For a read-only data retrieval tool, this is adequate but not thorough.

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 concise (~100 words), well-structured with a summary followed by parameter descriptions. It front-loads the main purpose and avoids redundancy.

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?

Given the presence of an output schema (not shown) and thorough parameter documentation in the description, the description is complete enough for correct usage. It covers the return content, parameters, and defaults.

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%, but the description provides detailed docstring for each parameter, including examples (e.g., 'CA', '037', '72') and explanations of defaults. This adds significant meaning beyond the raw 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 business establishment, employment, and payroll data by county. It distinguishes from siblings (compare_county_industries and get_state_business_summary) which focus on comparison and state-level summaries respectively.

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 explains that the tool returns data for a given geography and optional industry filter. It provides examples and default behaviors for optional parameters. However, it does not explicitly state when to use this tool versus siblings or when not to use it.

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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