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get_radius_demographics

Get aggregated Census demographics for radius rings around a US property address — the standard 1/3/5-mile trade-area format used in CRE site analysis. Aggregates every census tract whose centroid falls within each radius: population, household-weighted median income, employment rate, college attainment, housing vacancy, renter share, and median rent.

Use this for trade-area / site analysis. Use get_market_demographics for the single census tract immediately around the address.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressYesFull US property address (e.g. "1234 Main St, Charlotte, NC 28202")
radii_milesNoComma-separated radii in miles (default "1,3,5", each capped at 15)1,3,5

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.5/5.0
Behavior4/5

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

No annotations provided, so description carries full burden. It explains the aggregation method (census tracts whose centroid falls within each radius) and lists the demographic metrics. Could mention US-only limitation or data availability, but overall transparent.

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?

Three focused sentences: purpose, details, and usage alternative. No wasted words, well-organized.

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?

Input parameters are clearly covered. The output schema exists (not shown), so detailed return documentation is not needed, but description still lists the metrics. Usage context and alternatives are provided. Complete for decision-making.

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 coverage is 100% with clear descriptions of address and radii_miles. The description does not add new parameter semantics beyond what the schema already provides, though it gives helpful context about the aggregation logic. Baseline 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?

Clearly states the tool gets aggregated Census demographics for radius rings around a US property address. Specifically mentions the standard 1/3/5-mile trade-area format and lists the metrics returned, distinguishing it from the sibling get_market_demographics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

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

Explicitly tells when to use this tool (trade-area/site analysis) and when not to, with a direct alternative: 'Use get_market_demographics for the single census tract immediately around the address.'

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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TDQS

A4.3/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: lease documents, rent rolls, DCF models, Excel export, risk flags, deal memos, market data, rates, inflation, demographics at two geographic levels, and land screening at two scales. No two tools have overlapping purposes.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., abstract_lease, get_current_rates, screen_parcel_dd), making the tool surface predictable and easy to navigate.

Tool Count5/5

With 13 tools, the server is well-scoped for CRE investment analysis, covering lease abstraction, rent roll analysis, DCF modeling, market data, demographics, and land screening. The count is sufficient without being bloated.

Completeness5/5

The tool set covers the full lifecycle of CRE deal analysis: document parsing (lease, rent roll), financial modeling (DCF, Excel export), risk assessment (flag risks, parcel screens), market context (rates, inflation, demographics, CRE market data), and output (deal memo). No obvious gaps for the intended purpose.