Venue Extension
The hospitality extension for describing physical locations where bookings take place.
What is Venue?
A Venue represents any physical establishment that offers Bookables—hotels, restaurants, bars, spas, activity centres. It's the container that holds inventory and provides the context for what guests can expect.
Venue is a namespace extension to A2A Agent Cards that defines what AI agents need hospitality venues to express in order to make defensible recommendations and complete bookings.
Venue does not define a new protocol. It defines a structured vocabulary within existing A2A Agent Cards, extending the base Bookable pattern with hospitality-specific concepts.
Core Concepts
Venue extends the Bookable base pattern with additional blocks specific to physical hospitality establishments.
Identity
Verifiable existence: name, location, coordinates, domain ownership, and company registration.
Vibe
Subjective character structured for matching: essence, atmosphere, energy, formality.
Attributes
Factual, quantified characteristics: rooms, facilities, accessibility, policies.
Evidence
Proof supporting claims with provenance, verification status, and confidence scores.
Fit
Explicit intent alignment—what the venue is good for, and critically, what it is not.
Units
Bookable sub-entities: rooms, tables, areas. Each inherits from venue level.
Neighbourhood
Location context beyond coordinates: setting, walkability, proximity to points of interest.
Presentation
A2UI components for human-in-the-loop confirmation when agents present options.
Type Hierarchy
Venue defines a polymorphic type system enabling agents to work at different levels of abstraction.
Bookable (base)
└── Venue (hospitality)
├── Accommodation (Hotel, BnB, Hostel)
├── Eat (Restaurant, Cafe, Bar)
├── Experience (Museum, Tour, Activity)
└── Service (Spa, Salon)
All types inherit from Bookable. Agents MAY interact with any Bookable without knowing its specific type—if it's Bookable, you can book it.
Note: Stay is the booking lifecycle spec, not a venue type. When you book an Accommodation venue, the booking record follows the Stay lifecycle.
How Agents Use Venues
When planning a trip, agents query Venue data to make defensible recommendations.
Match Intent to Fit
Query fit.strong and fit.weak to find venues that align with user intent. A "romantic weekend" request should match venues declaring that intent as strong fit.
Verify Evidence Quality
Check evidence blocks for convergence, confidence, and verification status. Prefer claims with DMO verification or human observation over unverified self-reports.
Understand the Vibe
Use vibe to match subjective preferences. Is the guest looking for "lively" or "peaceful"? "Formal" or "casual"?
Check Facilities
Query attributes for specific requirements: pet-friendly, EV charging, accessible rooms, check-in times.
Present with Confidence
Use presentation components to render rich UI for human confirmation. Quote from answers to explain why this venue was recommended.
Venue Conformance Levels
Not every implementation needs everything. Venue defines progressive conformance levels.
| Level | Required Blocks | Use Case |
|---|---|---|
| Venue Core | identity, evidence, fit, actions | Minimum viable implementation |
| Venue Extended | Core + vibe, attributes, units, neighbourhood | Rich discovery |
| Venue Complete | Extended + presentation, answers | Full agent experience |
Start with Venue Core. The additional blocks accelerate agent decision-making but aren't required for basic functionality.
Why Declare Weak Fit?
Most hospitality systems only describe what venues are good for. Venue requires declaring what venues are NOT good for.
This matters because:
- Prevents bad recommendations before they happen
- Reduces book-then-complain-then-refund friction
- Signals honesty, which builds trust
- Improves agent recommendation precision
A venue declaring fit.weak: nightlife signals to agents not to recommend it for hen parties—before anyone books and is disappointed.
Learn More
Specification
Full technical specification with all field definitions and requirements.
Examples
Working JSON examples and complete venue payloads.