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AiAgentKarl

real-estate-data-mcp-server

get_nearby_amenities

Find nearby amenities such as schools, hospitals, parks, transit stops, supermarkets, restaurants, and pharmacies for any location via OpenStreetMap.

Instructions

Find nearby amenities around a location using OpenStreetMap.

Returns schools, hospitals, parks, transit stops, supermarkets, restaurants, and pharmacies within the specified radius.

Args: lat: Latitude of the location lon: Longitude of the location radius_m: Search radius in meters (default: 2000, max: 5000)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYes
lonYes
radius_mNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description should disclose behavioral traits. It mentions OpenStreetMap as the data source, but does not explain API rate limits, data freshness, caching, or any limitations on results. Lacks details on behavior beyond the basic output.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded with the core purpose. It lists parameters in a clear Args block. However, it could be slightly more structured (e.g., bullet points) for readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, the description doesn't need to explain return values. However, it lacks context about API dependencies (e.g., rate limits, if radius_m is optional) and does not mention the return format. Adequate but not fully comprehensive for a tool with no annotations.

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

Parameters4/5

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

Schema coverage is 0%, so the description must add meaning. It explains lat and lon as location coordinates and radius_m with default and max values. It also lists the types of amenities returned, which are not in the schema. This provides useful context beyond the schema.

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 purpose: find nearby amenities using OpenStreetMap. It lists specific amenity types (schools, hospitals, parks, etc.) and distinguishes itself from sibling tools like compare_areas, get_area_demographics, etc., which focus on other aspects.

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

Usage Guidelines3/5

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

The description implies usage for finding amenities but does not explicitly state when to use this tool versus alternatives like search_neighborhoods or get_housing_stats. No when-not or exclusion criteria are provided.

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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