Check World Cup 2026 specific short-term rental compliance requirements for the 16 US host cities. Returns special regulations, surge pricing rules, enhanced permit requirements, and safety standards that apply during the tournament. Pass the city name (required), optional property_id.
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes | World Cup host city | |
| property_id | No | Property UUID (optional) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds meaningful context about the return content (special regulations, surge pricing rules, enhanced permit requirements, safety standards), which goes beyond annotations and helps the agent understand what to expect.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and every clause adds value. No wasted words or redundant details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately explains what the tool returns (special regulations, surge pricing rules, enhanced permit requirements, safety standards) and explicitly mentions the 16 host cities. It is complete for a simple read-only query tool with one required parameter and clear annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both parameters (city and property_id), so the schema already explains them. The description only repeats that city is required and property_id optional, adding no new semantic meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks World Cup 2026 specific STR compliance for 16 US host cities, distinguishing it from generic compliance tools like check_str_permit_requirements or get_short_term_rental_regulations. It uses a specific verb and resource and mentions the unique scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use it (World Cup 2026 specific requirements during the tournament) but does not explicitly mention alternatives or when not to use it. The context is sufficient to guide selection, though exclusions are absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.
