CDC PLACES Health Data

get_county_measures

Get all CDC PLACES health measures for a county.

Returns up to 36 measures including health outcomes (diabetes, obesity,
heart disease, etc.), health behaviors (smoking, binge drinking), preventive
services (checkups, screenings), and health status indicators.

Args:
    county_fips: 5-digit county FIPS code (e.g. '53033' for King County, WA).
                 Must be a string, not an integer.
    year: Optional release year to filter by. Omit for the most recent data.

Input Schema

TableJSON Schema

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

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.1/5.0

Behavior3/5

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

Without annotations, the description carries full burden. It discloses the scope (up to 36 measures) and parameter behavior (omit year for most recent), but lacks details on error handling, authentication, rate limits, or what happens on invalid FIPS code.

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 and well-structured: purpose first, then a bullet-like summary of measures, then clear parameter docs. Every sentence adds value.

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?

Given the tool's simplicity (2 params, output schema exists), the description covers key points: what is returned, how to specify county and year. It could mention that the output schema defines the return format, but that's acceptable since the schema exists.

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 adds significant meaning: county_fips must be a 5-digit string (with example), year is optional and defaults to most recent. This goes well 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 gets all CDC PLACES health measures for a county, lists categories (health outcomes, behaviors, services), and distinguishes from siblings (e.g., get_tract_measures, compare_counties) by focusing on county-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 Guidelines3/5

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

The description implies use for a single county but does not explicitly state when to use this tool versus alternatives like compare_counties or search_measures. No when-not-to-use guidance is provided.

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

All CDC PLACES Health Data tools Inspect

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TDQS

A4.4/5.0

Disambiguation5/5

Each tool serves a distinct purpose: comparing counties, retrieving county measures, getting a single measure across state, tract-level data, and searching measures. No overlap in functionality.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (compare, get, get, get, search). Two tools are parallel (get_county_measures, get_tract_measures), and the others are clear and predictable.

Tool Count5/5

Five tools cover the essential operations for a focused health dataset: retrieval at county and tract levels, comparison, state-level query, and metadata search. The count is well-scoped.

Completeness4/5

The set covers main use cases, but lacks a tool to retrieve all measures for all counties in a state at once. Users must either call per county or per measure, which is a minor gap.

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