USDA Food Access

get_food_insecurity_indicators

Get food-related economic indicators as proxies for food insecurity by county.

Combines SNAP participation rate (B22001), poverty rate (B17001), and
median household income (B19013) to build a food insecurity risk profile.
Higher SNAP rates, higher poverty, and lower income correlate with greater
food insecurity. Useful for grant narratives demonstrating community need.

Args:
    state: Two-letter state abbreviation (e.g. 'WA', 'MS') or 2-digit FIPS code.
    county_fips: Three-digit county FIPS code (e.g. '033' for King County, WA).
                 Omit to get all counties in the state.
    year: ACS 5-year estimate year (default 2022). Data covers year-4 through year.

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?

With no annotations, the description carries the full burden. It explains the behavioral logic: it combines SNAP rates, poverty rates, and median income, and interprets higher/lower values as correlating with food insecurity. This adds meaningful context beyond a simple data fetch, though it doesn't mention limitations or potential edge cases.

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 front-loaded with the main purpose. Each sentence adds value, and the Args section is separated clearly for readability. It is not overly verbose.

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 output schema exists (so return format need not be described), this description covers the purpose, usage, and parameter semantics comprehensively. It is complete for a data retrieval tool.

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. The Args block explicitly defines each parameter: state accepts a 2-letter abbreviation or FIPS code, county_fips is a 3-digit code with an example, and year has a default and data range. This is much richer than 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 opens with a specific verb and resource: 'Get food-related economic indicators as proxies for food insecurity by county.' It clearly defines the tool's output (a risk profile) and distinguishes it from sibling tools that focus on agricultural data, food environment, or SNAP participation alone.

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 provides a clear use case: 'Useful for grant narratives demonstrating community need.' It implies when to use it (when assessing food insecurity risk) but does not explicitly mention alternatives or when not to use it relative to the sibling tools.

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

All USDA Food Access tools Inspect

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TDQS

A4.3/5.0

Disambiguation2/5

Three of the four tools (get_food_environment, get_food_insecurity_indicators, get_snap_participation) are highly overlapping, all operating at the county level with ACS data and combining SNAP, poverty, and income indicators. An agent would struggle to distinguish between them, as their purposes and outputs are nearly interchangeable. Only get_agricultural_data is clearly distinct.

Naming Consistency5/5

All tools follow a consistent 'get_<descriptive_noun>' pattern with snake_case. The verbs are uniform and the nouns clearly indicate the data being retrieved. This is a highly predictable naming scheme.

Tool Count5/5

Four tools is a well-scoped count for a specialized data access server. Each tool addresses a distinct aspect of food access data (agricultural production, food environment, food insecurity, SNAP participation), and the count is neither sparse nor overwhelming.

Completeness4/5

The server covers the core data needs for understanding food access: agricultural production, food environment risk, food insecurity indicators, and SNAP participation. Minor gaps exist, such as lack of food price or food store location data, but these are not fundamental to the server's stated purpose and agents can work around them.

Resources

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