CDC PLACES Health Data

get_measure_by_state

Get one CDC PLACES measure for all counties in a state.

Useful for comparing a specific health metric (e.g. DIABETES, OBESITY)
across all counties within a state. Returns the most recent data year.

Args:
    state_abbr: Two-letter state abbreviation (e.g. 'WA', 'CA').
    measure_id: PLACES measure ID (e.g. 'DIABETES', 'OBESITY', 'BPHIGH').
                Use search_measures to find valid IDs.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`measure_id`	Yes
`state_abbr`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.2/5.0

Behavior3/5

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

No annotations provided, so description carries burden. States it's a 'get' operation (read-only implied) and returns most recent data year. Does not disclose potential errors, rate limits, or response shape, but output schema exists externally.

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: one-line purpose, one-line use case, then structured Args section. No verbose explanations, front-loaded with key information. Every sentence is necessary.

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 simple tool (2 params, output schema exists), description covers purpose, usage, and parameter details. Missing error handling or data year specification, but sufficient for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage, but description adds meaningful semantics: explains state_abbr as two-letter abbreviation and measure_id as PLACES ID with examples, plus reference to search_measures. Compensates well for missing schema descriptions.

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 one CDC PLACES measure for all counties in a state, using a specific verb and resource. It distinguishes from siblings like compare_counties and get_county_measures by focusing on state-wide aggregation.

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?

Provides explicit context for usage: comparing a health metric across counties. Mentions returning most recent data year and refers to search_measures for valid IDs. Lacks explicit exclusions but gives clear when-to-use guidance.

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.

Resources

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