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geoagentic

by app.geoagentic

slovenia-realty-price

Market price statistics for a Slovenian cadastral municipality (KO), using ETN transaction data.

USE FOR:

  • "What are prices like in Ljubljana center (KO 1723)?"

  • "Market stats for KO 2242"

  • "What's the price per m² in KO 0168?"

NOT FOR: building- or parcel-specific valuation → not currently exposed by this tool. NOT FOR: parcel details, zoning, heritage → use cadastral-explorer or slovenia-cadastre. NOT FOR: live listings or asking prices → this uses historic transaction records only.

INPUT: --ko Required. KO ID (cadastral municipality), e.g. 1723.

OUTPUT: JSON with building and land price stats for the KO (median price, price/m², transaction count, year range) and a data_quality flag: high / medium / low / insufficient, based on transaction count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
koYesKO ID (cadastral municipality), e.g. 1723.

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, but the description discloses that the tool uses historic transaction records only (not live listings) and that the output includes a data_quality flag. While it does not cover rate limits or error handling, it provides enough behavioral context for an agent.

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 well-structured with clear sections (USE FOR, NOT FOR, INPUT, OUTPUT) and front-loaded with purpose and examples. Each sentence adds value, though it is slightly lengthy.

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 simplicity (one parameter, no output schema), the description adequately explains the output fields and data source (ETN transaction data). It is complete enough for an agent to understand what the tool returns and when to use it.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents the 'ko' parameter. The description does not add significant meaning beyond the schema (only repeats the KO ID example). Baseline 3 is appropriate.

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 provides market price statistics for Slovenian cadastral municipalities using ETN transaction data. It gives specific example queries and distinguishes from siblings by explicitly stating what it is NOT for (parcel details, zoning, listings).

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?

Includes explicit 'USE FOR' and 'NOT FOR' sections, with clear use cases and alternative tools mentioned (cadastral-explorer, slovenia-cadastre). This provides excellent guidance on when to use this tool versus others.

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