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census_population

Read-onlyIdempotent

Get total population for a US geography (state, county, ZIP/ZCTA, city, census tract, MSA, or national). Returns total, male, female, and median age. Used for market sizing, location intelligence, demographic analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
msaNo5-digit Metropolitan Statistical Area code. Required for msa level.
yearNoACS 5-year endpoint year (default 2023).
zctaNo5-digit ZIP Code Tabulation Area. Required for zcta level.
levelYesGeography level: 'us', 'state', 'county', 'zcta' (ZIP), 'place' (city), 'tract', 'msa'.
placeNoCensus place FIPS (city). Required for place level.
stateNo2-letter state code (e.g. 'TX') or 2-digit FIPS. Required for state/county/place/tract levels.
tractNo6-digit census tract code. Use '*' for all tracts in a county.
countyNo3-digit county FIPS. Use '*' for all counties in a state. Required for county/tract levels.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With annotations already declaring readOnlyHint, idempotentHint, and destructiveHint=false, the description adds meaningful behavioral context by listing the returned metrics (total, male, female, median age) and the supported geography scope. This helps the agent predict what the call will produce without an output schema.

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 three sentences with no wasted words: action and scope first, then return values, then use cases. It is appropriately sized for a data-retrieval tool and front-loads the most important information.

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?

The description covers the core outputs, supported geographies, and typical use cases, which is sufficient given the rich schema and read-only annotations. It could be slightly more complete by explicitly differentiating itself from census_demographics, but an agent can still invoke it correctly with the schema's parameter descriptions.

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?

Schema description coverage is 100%, so the schema already documents all 8 parameters and their conditional requirements. The description adds little parameter-specific meaning beyond restating geography levels, which are already captured in the level enum and parameter 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 opens with a specific verb and resource: 'Get total population for a US geography,' then enumerates all supported geography levels. It also distinguishes itself from sibling census tools by specifying the exact outputs (total, male, female, median age), which clarifies its narrow population-focused 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 provides clear usage context by stating it is 'Used for market sizing, location intelligence, demographic analysis.' It does not explicitly name alternative tools or exclusion criteria, but the use cases give an agent enough context to select it over broader census or demographic tools.

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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