Get detailed real estate market statistics for a specific location including demographics, housing data, Zillow market trends, investment metrics, and lending availability. Data from Census ACS 2023 and Zillow Feb 2026. USDV Capital — Your Real Estate CFO.
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes | State name or 2-letter code | |
| location | Yes | City, county, or state name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it as read-only and idempotent. The description adds useful context about data sources (Census ACS 2023, Zillow Feb 2026) and the breadth of data, but does not disclose output format or any potential limitations. This goes beyond annotations but not significantly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the primary purpose. The first sentence is dense with useful information. The branding at the end (USDV Capital — Your Real Estate CFO) is non-essential but does not significantly hurt conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only market statistics tool with two simple parameters, the description covers what data will be returned, data sources, and location scope. It lacks mention of output format, but the absence of an output schema makes this less critical. The level of detail is adequate for an agent to understand the tool's function.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the two parameters, and descriptions exist for both. The tool description does not add extra meaning beyond the schema, so it meets the baseline but does not elevate it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets detailed real estate market statistics for a specific location, listing specific data categories. This distinguishes it from sibling tools like markets-compare (comparison) and markets-screener (screening) by emphasizing location-specific stats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like markets-search or markets-compare. The description does not mention exclusions or alternatives, so the agent receives no proactive selection help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes, especially the calculators and utilities. The markets-* group has five tools that all return market data, but each has a distinct focus (compare, nearby, screener, search, stats) with descriptions that clarify the differences. Overall, an agent can generally tell them apart, though the market tools could still cause minor confusion.
The naming convention is consistent across categories using lowercase with hyphens and a prefix (action-, calc-, deal-, eligibility-, markets-, util-). Within categories there is slight inconsistency, such as action-consultation (noun) vs action-prequalify (verb) vs action-send_report (verb_noun), but the overall pattern is predictable and readable.
With 23 tools, the server covers a broad range of real estate CFO services: property analysis, market intelligence, eligibility, and client actions. This is slightly on the heavy side but each tool serves a distinct purpose within the domain. It could be trimmed, but the count is not unreasonable given the scope.
The tool set covers the core lifecycle of a real estate deal: market research, property-level analysis, calculators for various strategies, eligibility checking, and client engagement actions. Minor gaps exist—such as no tool for tracking existing deals or a general mortgage payment calculator—but the main workflows are well supported. Completeness is strong for the stated purpose.
