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cyntrica

Gov Data MCP

by cyntrica

cdc_places_city

Read-only

Retrieve CDC PLACES health indicators for any U.S. city: obesity, diabetes, smoking, depression, and 30+ measures. Get city-level data by specifying city name and state.

Instructions

Get city-level health indicators from CDC PLACES — obesity, diabetes, smoking, depression, sleep, blood pressure, mental health, and 30+ more measures for every U.S. city with population > 50,000. Each row contains ALL measures for a city as separate columns (e.g. obesity_crudeprev, diabetes_crudeprev).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoCity name (partial match): 'Los Angeles', 'Chicago'
limitNoMax records (default 200)
stateNoTwo-letter state code: 'NY', 'CA', 'TX'
Behavior4/5

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

The readOnlyHint annotation already covers the safety profile, and the description adds meaningful value beyond that by disclosing the data structure (one row per city, all measures as separate columns) and the population threshold. It does not mention pagination or rate limits, but for a read-only data lookup, the added scope and structure context is sufficient.

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 exactly two sentences, with the first sentence front-loading the verb, resource, and key measures, and the second sentence clarifying the row-level data shape. Every clause adds useful information, with no tautology or filler.

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 (3 optional parameters, no output schema), the description covers the essential context: what data is returned, its granularity, and its structure. It complements the readOnlyHint annotation and detailed schema without needing to explain return values. The only minor gap is that it doesn't specify what happens when no city or state is provided, but the schema's parameter descriptions handle that implicitly.

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

Parameters3/5

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

The input schema provides detailed descriptions for all three parameters (city with partial match, limit with default, state with code examples), achieving 100% schema description coverage. The tool description does not add further parameter-specific meaning beyond what the schema already explains, so the baseline score of 3 is appropriate.

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's action ('Get'), resource ('city-level health indicators from CDC PLACES'), and scope ('every U.S. city with population > 50,000'). It lists specific measures and distinguishes itself from the sibling tool cdc_places_health by focusing on city-level data rather than a broader geographic scope.

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 implies when to use this tool by emphasizing city-level granularity and the comprehensive set of measures, giving clear context for selecting it over other CDC tools. However, it does not explicitly name alternatives or provide exclusion criteria, so it stops short of offering direct guidance on 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.

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