Get aggregated market, sheriff, sold, and investment stats for one area.
Args:
name: Neighborhood or municipality name (e.g. "Point Breeze North").
area_type: "neighborhood" or "municipality".
Returns counts, median prices, average cap rate, and sold-comp metrics
for the area.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| area_type | No | neighborhood |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the return categories and clarifies that stats are aggregated for a single area, but omits details like default behavior for area_type, error handling, or explicit read-only confirmation. The 'Get' verb implies non-mutating behavior.
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 two sentences plus an Args block, front-loaded with the primary purpose and returning a clear list of metrics. No redundant or unnecessary content.
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?
While the description covers the main purpose and parameters, it lacks detail on the exact return structure (e.g., what constitutes 'counts' or 'sold-comp metrics') and does not provide usage context relative to sibling tools. Given no output schema, this is a notable gap for an agent parsing results.
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?
The description provides semantic context absent from the schema: 'name' is described as a neighborhood or municipality with an example, and 'area_type' is constrained to 'neighborhood' or 'municipality'. This fully compensates for the schema's lack of field descriptions.
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 uses a specific verb ('Get') and identifies the resource ('aggregated market, sheriff, sold, and investment stats for one area'). It also clarifies scope ('for one area'), distinguishing it from sibling tools like top_investment_areas which likely cover multiple areas.
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?
The description implies usage when area-level aggregated stats are needed, and provides parameter guidance, but does not explicitly mention alternatives or conditions when not to use. No exclusionary or alternative tool references are given.
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 are clearly distinct, but analyze_brrrr overlaps with get_property when given an address and strategy=brrrr, since both can return a BRRRR analysis. The ad-hoc input option for analyze_brrrr and the broader strategy support in get_property help clarify, yet the boundary is not fully crisp.
Tool names are mostly snake_case with a verb_object pattern (analyze_brrrr, get_comps, get_property, search_deals), but area_stats and top_investment_areas are noun phrases, and whoami is a standalone command. These minor deviations are easy to predict and remember.
With 7 tools, the server is well-scoped for a real estate deal analysis domain. Each tool covers a distinct high-level task (search, analysis, comps, stats, ranking, identity) without unnecessary redundancy or excessive fragmentation.
The surface covers the core lifecycle: searching deals, analyzing properties (flip, rental, brrrr), pulling comps, getting area stats, and ranking areas. A minor gap is the lack of a dedicated 'analyze_flip' or 'analyze_rental' tool, but get_property with strategy handles those cases, so no dead ends.