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places_search

Find points of interest, businesses, or landmarks near a coordinate. Search by category keyword or name, results sorted by distance.

Instructions

Find points of interest, businesses, and landmarks near a geographic coordinate.

Returns: array of { name, lat, lon, categories: [string], address, distance_m }.

QUERY: Use category keywords (restaurant, pharmacy, hospital, supermarket, ATM, petrol station, parking) or specific names ("Starbucks", "IKEA"). RADIUS: Default 1000m (1km). Increase for rural areas, decrease for dense urban. Max ~50000m. RESULT ORDER: Sorted by distance from the search center, nearest first.

USE FOR: "Find nearest X", store locators, POI search, route stop suggestions. DO NOT USE: For address lookups — use geocode instead. For administrative boundaries — use point_in_polygon.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesCategory or name to search for.
latYesSearch center latitude. Range: -90 to 90.
lonYesSearch center longitude. Range: -180 to 180.
radiusNoSearch radius in metres. Default: 1000. Increase for rural areas. Max ~50000.
limitNoMax results to return. Default 10, max 20.
countriesNoOptional ISO country codes to restrict search. Example: "DE,AT".
Behavior4/5

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

With no annotations, the description carries full burden. It discloses return format, default/max radius, result ordering, and query hints. Lacks mention of authentication or rate limits but is transparent enough for a search tool.

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?

Well-structured with clear sections (QUERY, RADIUS, RESULT ORDER, USE FOR, DO NOT USE). Every sentence is informative with no redundancy.

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?

Given 6 parameters and no output schema, the description covers all key aspects: purpose, parameters, expected output format, and usage boundaries. Examples further enhance completeness.

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

Parameters5/5

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

Schema description coverage is 100%, and the description adds value beyond the schema: default radius with usage context (rural vs urban), max radius, query examples, and country format example.

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 points of interest, businesses, and landmarks near a geographic coordinate.' It specifies the return format and distinguishes from siblings like geocode and point_in_polygon in the DO NOT USE section.

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?

Explicit usage guidance: 'USE FOR' lists common tasks, 'DO NOT USE' gives alternatives (geocode, point_in_polygon). Also provides tips for query and radius adjustments.

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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