Property Governance

AdCP Property Governance standardizes identification, authorization, enrichment, and selection of advertising properties across all media channels.

Property Governance standardizes how advertising properties (websites, apps, CTV, podcasts, billboards) are identified, authorized, enriched with data, and selected for campaigns. Ships in 3.0 as the property-lists specialism under the governance protocol.

Property lists and collection lists together form the inventory list system — property lists control where ads run (technical surfaces), while collection lists control what content ads run in (programs, shows, series). Both are setup-time artifacts managed by governance agents with the same lifecycle pattern.

adagents.json is intentionally broader than ads.txt: it can describe not just which sales agents are present, but which properties, placements, and delegated sales paths they are actually authorized to make available. For a side-by-side comparison, see Why adagents.json is more expressive than ads.txt.

Overview

Property Governance addresses five distinct concerns:

Concern	Question	Owner	Mechanism
Property Identity	What properties exist?	Publishers	adagents.json properties array
Sales Authorization	Who can sell this property?	Publishers	adagents.json authorized_agents with delegation_type
Property Data	What do we know about this property?	Data providers	Governance agents via get_adcp_capabilities
Property Selection	Which properties meet my requirements?	Buyers	Property lists with filters

The first three are publisher-side declarations via adagents.json. The last two are buyer-side operations that consume property data from governance agents.

Authorization is bilateral — publishers declare authorized agents in adagents.json (with delegation_type), and operators declare their property portfolio in brand.json (with relationship). Both sides must agree for the supply path to be verified. This is the AdCP equivalent of ads.txt + sellers.json. See ad networks for how this works.

Publisher Side: adagents.json

Publishers declare their properties, authorize sales agents, and reference governance agents via /.well-known/adagents.json:

{
  "$schema": "https://adcontextprotocol.org/schemas/v3/adagents.json",
  "properties": [
    {
      "property_id": "example_site",
      "property_type": "website",
      "name": "Example Site",
      "identifiers": [{"type": "domain", "value": "example.com"}]
    }
  ],
  "authorized_agents": [
    {
      "url": "https://agent.example.com",
      "authorized_for": "Official sales agent",
      "authorization_type": "property_ids",
      "property_ids": ["example_site"],
      "delegation_type": "direct"
    }
  ],
  "property_features": [
    {
      "url": "https://api.sustainability-vendor.example",
      "name": "Sustainability Vendor",
      "features": ["carbon_score", "green_media_certified"]
    },
    {
      "url": "https://api.quality-vendor.example",
      "name": "Quality Vendor",
      "features": ["mfa_score", "ad_load_rating", "page_speed"]
    }
  ]
}

Governance Agent Discovery via property_features

The property_features array solves a key discovery problem: how does a buyer know which governance agents have data about a given property?

Without property_features, buyers would need to query every possible governance agent to find out who has compliance, sustainability, or quality data. With property_features, publishers declare these relationships upfront:

Field	Purpose
url	Governance agent’s API endpoint
name	Human-readable agent name
features	Feature IDs this agent provides (e.g., carbon_score, mfa_score)
publisher_id	Optional identifier for looking up this publisher at the agent

Example use cases:

• Sustainability: Publisher declares a carbon measurement vendor tracks their emissions
• Quality: Publisher declares a verification vendor measures MFA score and ad density
• Consumer experience: Publisher declares a vendor that tracks page speed and ad load

Buyers read property_features from adagents.json, then query only the relevant governance agents for detailed data.

See the adagents.json Tech Spec for complete documentation including examples and the discovery workflow.

Buyer Side: Property Data and Selection

Property Data Providers

Governance agents provide data about properties - compliance scores, brand suitability ratings, sustainability metrics, consumer experience scores, etc. They advertise their capabilities via get_adcp_capabilities in the governance.property_features section:

{
  "governance": {
    "property_features": [
      { "feature_id": "mfa_score", "type": "quantitative", "range": { "min": 0, "max": 100 } },
      { "feature_id": "coppa_certified", "type": "binary" },
      { "feature_id": "carbon_score", "type": "quantitative", "range": { "min": 0, "max": 100 } }
    ]
  }
}

Buyers send property lists to these agents, and the agents filter and score the properties based on their specialized data. Different agents specialize in different data:

• Brand suitability providers (content classification, risk scoring)
• Quality measurement (MFA score, ad density, fraud detection)
• Sustainability providers (carbon scoring, green media certification)
• Consumer experience (page speed, ad load, layout shift)

Property Selection via Governance Agents

Buyers create property lists on governance agents - the agents manage these lists and apply their filtering logic:

{
  "tool": "create_property_list",
  "arguments": {
    "name": "Q1 Campaign - UK Premium",
    "base_properties": [
      {
        "selection_type": "publisher_tags",
        "publisher_domain": "raptive.com",
        "tags": ["premium_news"]
      }
    ],
    "filters": {
      "countries_all": ["UK"],
      "channels_any": ["display", "video"],
      "feature_requirements": [
        { "feature_id": "mfa_score", "min_value": 70, "max_value": 100 }
      ]
    },
    "brand": {
      "domain": "toybrand.com"
    }
  }
}

When you provide a brand reference, governance agents resolve the brand identity and automatically apply appropriate rules (COPPA for children’s brands, content filtering based on industry, etc.).

A buyer agent typically works with multiple governance agents (brand suitability, quality, sustainability) and aggregates/intersects their results into a final compliant list.

How It Fits Together

The Complete Flow

1. Publisher declares properties, sales agents, AND governance agents in adagents.json
2. Buyer discovers governance agents by reading property_features from adagents.json
3. Buyer queries each governance agent’s get_adcp_capabilities for detailed capabilities
4. Buyer creates property lists on each governance agent with filters and brand references
5. Governance agents evaluate properties and notify buyer via webhooks when lists change
6. Buyer aggregates results into a final compliant list
7. Buyer shares property list reference with sellers (with auth token)
8. Seller caches resolved list for bid-time decisions

Sharing Property Lists with Sellers

Once a buyer has a compliant property list, they share it with sellers:

1. Get a list reference: The buyer agent exposes the list via get_property_list
2. Issue an auth token: The buyer generates a token that authorizes access to the list
3. Pass to seller: Include property_list_ref with auth_token in product discovery or media buy requests
4. Seller caches locally: Sellers fetch and cache the resolved list for bid-time decisions
5. Webhooks for updates: When the list changes, sellers are notified to refresh their cache

{
  "property_list_ref": {
    "agent_url": "https://buyer-agent.example.com",
    "list_id": "pl_q1_uk_premium",
    "auth_token": "eyJhbGciOiJIUzI1NiIs..."
  }
}

Sellers use this reference in get_products to filter available inventory:

{
  "tool": "get_products",
  "arguments": {
    "brief": "UK video inventory for Q1",
    "property_list_ref": {
      "agent_url": "https://buyer-agent.example.com",
      "list_id": "pl_q1_uk_premium",
      "auth_token": "..."
    }
  }
}

Relationship to Other Protocols

Property Governance + Media Buy

The Media Buy Protocol consumes property lists at multiple stages:

• Product discovery: Pass property_list_ref to get_products to filter inventory to compliant properties
• Media buy creation: Reference property lists to constrain where ads can run
• Authorization: adagents.json validates agent authority to sell

Property Governance + Signals

Both protocols operate on properties but serve different purposes:

Signals Protocol	Property Governance
Audience/contextual data	Property metadata and compliance
”Who should see this ad?"	"Where can this ad run?”
Signal activation	Property filtering

Tasks

Discovery

• get_adcp_capabilities: Discover governance capabilities including property features (protocol-level task)

Property List Management

• create_property_list: Create a new property list on a governance agent
• get_property_list: Retrieve resolved properties (with caching guidance)
• update_property_list: Modify filters or base properties
• delete_property_list: Remove a property list

Getting Started

Publishers:

1. Create /.well-known/adagents.json with property definitions
2. Authorize sales agents for your properties
3. Declare governance agents in property_features (sustainability vendors for carbon, quality vendors for MFA and ad load, suitability vendors for content classification, etc.)

Buyers:

1. Discover governance agents by reading property_features from publishers’ adagents.json files
2. Query each governance agent’s get_adcp_capabilities for capabilities
3. Create property lists on relevant governance agents with filters and brand references
4. Aggregate results into a final compliant list
5. Share property list references with sellers (with auth tokens)

Governance Agent Implementers:

1. Implement get_adcp_capabilities to advertise your capabilities in governance.property_features
2. Implement property list CRUD operations
3. Support webhooks to notify buyers when evaluations change
4. Work with publishers to get listed in their property_features
5. See the Protocol Specification for implementation details

See the Protocol Specification for detailed implementation guidance.