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geoagentic

by app.geoagentic

geo-osm

Find nearby places on OpenStreetMap (cafes, ATMs, shops, parks, etc.).

CRITICAL: The 'tags' argument MUST be passed as a single stringified JSON text block, NOT a nested JSON object. Example: "{"amenity":"cafe"}"

USE FOR:

  • "Find a cafe near X"

  • "Are there any ATMs close to Y?"

  • "Show me supermarkets near Z"

NOT FOR: directions, geocoding, Wikipedia, isochrones.

EXAMPLE: User: "Find cafes near Koper station" → --lat 45.548 --lon 13.730 --tags '{"amenity":"cafe"}' --dist 300

COMMON TAGS: amenity: cafe, restaurant, atm, pharmacy, parking shop: supermarket, bakery, convenience tourism: hotel, museum, attraction

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude of the search center.
lonYesLongitude of the search center.
distNoSearch radius in metres (max 10 000).
tagsYesJSON OSM tag filter passed strictly as a stringified/escaped JSON string. DO NOT pass a JSON object. Example format: '{"amenity":"cafe"}'
limitNoMax results (1–50).
timeoutNoHard timeout in seconds (max 60).

TDQS

A4.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the critical tag format requirement, search radius limits (max 10,000m), hard timeout (max 60s), and result limit (1-50). However, it does not describe the response structure or whether results include coordinates, names, etc., which would improve transparency.

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?

The description is well-structured with sections (CRITICAL, USE FOR, NOT FOR, EXAMPLE, COMMON TAGS). Every section is concise and informative, with no wasted sentences. The use of bold for critical information enhances readability.

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 the tool's complexity (6 parameters, no output schema, no annotations), the description is remarkably complete. It covers purpose, usage guidelines, parameter specifics, an example, and common tag values. The agent has sufficient information to invoke the tool correctly.

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?

Although the input schema covers all 6 parameters with descriptions, the explanation adds significant value: it details the exact format for the tricky 'tags' parameter (stringified JSON), provides an example, and lists common OSM tags by category. This goes well 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 finds nearby places on OpenStreetMap (cafes, ATMs, etc.), specifying the resource (OSM) and action (find nearby places). It distinguishes itself from siblings by explicitly listing what it is not for (directions, geocoding, Wikipedia, isochrones).

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?

The description provides explicit use cases ('Find a cafe near X'), a clear 'NOT FOR' list, and a concrete example with parameters. This guides the agent on when to use this tool versus alternatives.

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

A3.7/5.0
Disambiguation4/5

Most tools have clearly distinct purposes (geocoding vs routing vs POI search). However, the multiple Slovenian cadastral tools (simple, deep, wfs-expert) overlap in functionality, potentially confusing an agent on which to use for a given task.

Naming Consistency3/5

Tools within subgroups like 'geo-*' follow a consistent verb_noun pattern, and 'slovenia-*' tools use a noun_adjective pattern. However, across the whole set there is no unified naming convention, mixing prefixes like 'eu-', 'events-', 'hikes-', and 'hostel-'.

Tool Count4/5

With 16 tools, the server is slightly above the ideal range (3-15) but still well-scoped. Each tool addresses a distinct geographic need, although the breadth across many domains (transit, cadastre, weather, hostels) feels a bit broad.

Completeness4/5

The tool set covers core geographic operations (geocoding, routing, POI, isochrones, reverse geocoding) plus specialized Slovenian data and travel amenities. Minor gaps exist, such as lack of general worldwide POI beyond OSM or event discovery beyond Luma, but overall it is comprehensive for its domain.

Resources