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geoagentic

by app.geoagentic

hostel-prices

Live hostel and budget accommodation prices from Hostelworld for any city worldwide. USE FOR:

  • "What are the cheapest hostels in Paris next week?"

  • "Find dorm beds in Bangkok for 3 nights from July 10"

  • "Compare hostel prices in Ljubljana vs Belgrade"

  • Budget travel planning, accommodation cost context, backpacker routing RETURNS: Per-property dorm and private room prices per night, guest ratings, free cancellation flag, and summary stats (floor/avg/top price). CRITICAL INSTRUCTIONS FOR AGENT:

  • Always pass date as YYYY-MM-DD format.

  • currency defaults to EUR.

  • Use summary.floor for "cheapest" queries, summary.average for general cost context.

  • free_cancellation=true properties are preferable for uncertain itineraries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesCity name, e.g. Ljubljana, Paris, Bangkok, New York
dateYesCheck-in date in YYYY-MM-DD format
guestsNoNumber of guests, e.g. 22
nightsNoNumber of nights to stay, e.g. 35
currencyNoCurrency code: EUR, USD, GBP, etc.EUR

TDQS

A4.4/5.0
Behavior4/5

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

Since no annotations exist, the description discloses important behavioral traits: it requires YYYY-MM-DD date format, defaults currency to EUR, and explains how to interpret fields like summary.floor vs summary.average. It also mentions the free_cancellation flag. It does not explicitly state it is read-only, but the context implies no side effects. This is sufficient for safe usage.

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: starting with a clear purpose statement, followed by use cases, return description, and critical instructions. It is front-loaded and every sentence adds value. A slight reduction from 5 because it is a bit verbose with the use case list, but overall efficient.

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 no output schema, the description provides a good overview of return values: per-property prices, guest ratings, free cancellation flag, and summary stats. It also includes critical instructions for date format, currency, and field interpretation. This fully equips an agent to use the tool correctly.

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 100% with descriptions for all 5 parameters. The description adds value by clarifying date format, default currency, and usage of summary fields, which are not present in schema descriptions. This goes beyond the baseline of 3.

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 'Live hostel and budget accommodation prices from Hostelworld for any city worldwide.' This specifies the verb (get/list) and resource (hostel prices), and the scope is broad but defined. No sibling tool covers accommodation prices, so it stands out.

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

Usage Guidelines4/5

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

The description provides multiple example queries (cheapest hostels, dorm beds, compare cities) and explicit use cases like budget travel planning. It also gives instructions on how to interpret summary fields for specific queries. However, it does not explicitly state when not to use it or name alternatives, so it falls short of a 5.

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.

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