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lilo Vacation Rentals

by io.github.lilo-property

search_world_cup_rentals

Read-only

Search for vacation rentals in FIFA World Cup 2026 host cities. Returns properties with stadium proximity information, match schedules, and expected demand surge data. Use this when a traveler is looking for accommodation for World Cup 2026 matches. Supports 11 US host cities: Miami, New York, Los Angeles, Dallas, Philadelphia, Atlanta, Houston, Seattle, San Francisco, Boston, Kansas City.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesWorld Cup 2026 host city (e.g. 'Miami', 'Philadelphia')
limitNoMax results to return (default 10, max 50)
check_inNoCheck-in date (YYYY-MM-DD format, tournament runs Jun 11 - Jul 19, 2026)
check_outNoCheck-out date (YYYY-MM-DD format)
group_sizeNoNumber of guests in the group

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful context about result contents ('stadium proximity information, match schedules, and expected demand surge data') and the geographic scope, which goes beyond the annotations without contradicting them.

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?

Four tightly written sentences: action, return contents, use trigger, and supported cities. No filler or redundancy; key information is front-loaded in the first sentence.

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?

For a read-only search tool with 5 params and no output schema, the description covers purpose, when to use, supported city values, and return data categories. Combined with the schema's parameter details and read-only annotations, this is sufficient for an agent to select and invoke 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 description coverage is 100%, so baseline is 3. The description adds value by enumerating all 11 valid host cities, which is not fully captured by the schema's 'e.g.' examples. This helps the agent select a valid city value.

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 opens with 'Search for vacation rentals in FIFA World Cup 2026 host cities' and specifies unique return content: 'stadium proximity information, match schedules, and expected demand surge data.' This clearly distinguishes it from generic sibling tools like search_vacation_rentals.

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?

It provides an explicit trigger: 'Use this when a traveler is looking for accommodation for World Cup 2026 matches' and lists the 11 supported host cities. However, it does not name alternative tools or state when not to use this tool.

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

A3.6/5.0
Disambiguation2/5

There is significant overlap and redundancy among tools, causing ambiguity. For example, analyze_booking_threat_risk, analyze_guest_communication_risk, and analyze_guest_interaction_risk are aliases or near-duplicates, and multiple tools like get_vacation_rental_details and fetch_vacation_rental_details appear to serve the same purpose. This makes it difficult for an agent to choose the correct tool without confusion.

Naming Consistency4/5

Most tools follow a consistent verb_noun pattern (e.g., check_vacation_rental_availability_and_pricing, get_vacation_rental_details), which aids readability. However, there are minor deviations, such as some tools using 'analyze' vs. 'assess' or 'detect' for similar risk functions, and a few tools like 'ingest_philadelphia_public_records' use a different verb style, but overall the naming is largely predictable.

Tool Count2/5

With 67 tools, the count is excessive for a vacation rental server, leading to bloat and potential overwhelm. Many tools could be consolidated (e.g., multiple risk analysis tools, duplicate property detail fetchers), and the scope feels unfocused, including niche tools like those for Philadelphia events or World Cup compliance that might be better handled as parameters in broader tools.

Completeness5/5

The tool set provides comprehensive coverage for the vacation rental domain, including booking, risk assessment, compliance, maintenance, evidence management, and guest interactions. There are no obvious gaps; it supports full CRUD/lifecycle operations and specialized workflows, ensuring agents can handle most scenarios without dead ends.

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