Campaign Governance specification

Status: Request for Comments Last Updated: March 2026 The key words “MUST”, “MUST NOT”, “REQUIRED”, “SHALL”, “SHALL NOT”, “SHOULD”, “SHOULD NOT”, “RECOMMENDED”, “MAY”, and “OPTIONAL” in this document are to be interpreted as described in RFC 2119. This document defines the data models, validation logic, and integration patterns for Campaign Governance.

Campaign plan

The campaign plan is the source of truth for all validation. Plans are pushed to the governance agent via sync_plans and define the plan parameters for a campaign — budget limits, channels, flight dates, and plan markets. The governance agent resolves applicable policies from the brand’s compliance configuration. Plans can also reference registry policies directly via policy_ids and include campaign-specific rules via custom_policies.

{
  "plan_id": "plan_q1_2026_launch",
  "brand": {
    "domain": "acmecorp.com"
  },
  "objectives": "Drive awareness for spring product launch among 25-54 adults in the US, focusing on premium video and high-impact display.",
  "budget": {
    "total": 500000,
    "currency": "USD",
    "authority_level": "agent_limited",
    "per_seller_max_pct": 40,
    "reallocation_threshold": 25000
  },
  "channels": {
    "required": ["olv"],
    "allowed": ["olv", "display", "ctv", "audio"],
    "mix_targets": {
      "olv": { "min_pct": 40, "max_pct": 70 },
      "display": { "min_pct": 10, "max_pct": 30 },
      "ctv": { "min_pct": 0, "max_pct": 20 },
      "audio": { "min_pct": 0, "max_pct": 10 }
    }
  },
  "flight": {
    "start": "2026-03-15T00:00:00Z",
    "end": "2026-06-15T00:00:00Z"
  },
  "countries": ["US"],
  "policy_ids": ["us_coppa", "alcohol_advertising"],
  "custom_policies": ["No competitor brand adjacency"],
  "approved_sellers": null,
  "ext": {}
}

Budget authority levels

Level	Meaning
`agent_full`	Agent can execute any spend within the total budget without human approval
`agent_limited`	Agent can execute within thresholds but MUST escalate large changes (defined by `reallocation_threshold`)
`human_required`	Every spend commitment requires human approval

Channel mix targets

The mix_targets field defines acceptable allocation ranges. The governance agent validates that aggregate spend across all media buys stays within these ranges. A create_media_buy that would push video spend above 70% of total budget triggers a conditions or escalated status.

Delegations

Plans can include a delegations array that specifies which agents are authorized to execute against the plan and with what constraints. This makes the principal-agent relationship between brand and agency explicit in the protocol.

{
  "plan_id": "plan_q1_2026_launch",
  "brand": { "domain": "acmecorp.com" },
  "delegations": [
    {
      "agent_url": "https://buying.pinnacle-media.com",
      "authority": "full",
      "budget_limit": { "amount": 300000, "currency": "USD" },
      "markets": ["FR", "DE", "GB"],
      "expires_at": "2026-06-30T00:00:00Z"
    },
    {
      "agent_url": "https://buying.nova-agency.com",
      "authority": "execute_only",
      "markets": ["US"],
      "expires_at": "2026-06-30T00:00:00Z"
    }
  ]
}

Authority levels:

Level	Meaning
`full`	Can execute any action within the delegation’s budget and market constraints
`execute_only`	Can execute pre-approved actions but cannot initiate new campaigns or reallocate budget
`propose_only`	Can propose actions for governance review but cannot execute without explicit approval

When delegations are present, the governance agent validates that the caller URL in check_governance matches a delegation’s agent_url before approving actions. Matching is by exact URI comparison (case-sensitive, after normalization per RFC 3986). An agent requesting a media buy in France must have a delegation that includes France in its markets. An agent with execute_only authority cannot reallocate budget between channels. When delegations are absent, the governance agent does not restrict which agents can act on the plan.

Portfolio governance

For holding companies and multi-brand organizations, a plan can include a portfolio object that defines cross-brand constraints. Portfolio plans govern member plans — any action validated against a member plan is also validated against the portfolio plan’s constraints.

{
  "plan_id": "portfolio_q1_2026_global",
  "brand": { "domain": "acmecorp.com" },
  "objectives": "Global Q1 media governance across all Acme brands",
  "budget": { "total": 50000000, "currency": "USD", "authority_level": "agent_limited" },
  "flight": { "start": "2026-01-01T00:00:00Z", "end": "2026-06-30T00:00:00Z" },
  "countries": ["US", "GB", "FR", "DE", "JP"],
  "portfolio": {
    "member_plan_ids": ["plan_sparkle_q1", "plan_glow_q1", "plan_nova_q1"],
    "total_budget_cap": { "amount": 50000000, "currency": "USD" },
    "shared_policy_ids": ["eu_gdpr_advertising", "eu_ai_act_article_50"],
    "shared_exclusions": [
      "No advertising on properties owned by competitor holding companies"
    ]
  }
}

Portfolio constraints:

total_budget_cap: Maximum aggregate spend across all member plans. The governance agent tracks committed budget across all member plans and denies actions that would exceed the cap.
shared_policy_ids: Registry policies enforced across all member plans, regardless of individual brand compliance configuration. Corporate-level regulations that no brand team can override.
shared_exclusions: Natural language exclusion rules applied to all member plans.

The governance agent validates member plan actions against both the member plan’s own constraints and the portfolio plan’s constraints. A denial from either level blocks the action. When a portfolio plan references a member_plan_id that the governance agent does not yet recognize, the governance agent SHOULD accept the portfolio plan and begin enforcing portfolio constraints as member plans are synced. This allows portfolio plans to be synced before their member plans without requiring a specific ordering.

Concurrency: An orchestrator may send create_media_buy requests to multiple sellers simultaneously, each triggering a committed check. Budget checks are point-in-time and do not reserve budget, so concurrent approvals may together exceed the plan budget. The governance agent detects overspend at outcome reporting time. To prevent concurrent overspend, use delegations with per-agent budget_limit to partition the budget across executing agents.

Brand compliance configuration

Compliance policies live at the brand level, not in individual campaign plans. The brand’s policy team configures the brand’s compliance profile, and the governance agent resolves it when processing plans for that brand.

The schema and hosting mechanism for brand compliance configuration are under development by the AgenticAdvertising.org Governance Working Group. The following describes the conceptual model; implementations may vary.

A brand’s compliance configuration contains two kinds of policies:

Registry policies: References to standardized policies in the AdCP policy registry, identified by ID. Each reference MAY include configuration parameters that customize the policy for the brand.
Custom policies: Brand-specific rules expressed as natural language strings, evaluated by the governance agent using the same approach as prompt-based policies.

The policy team selects registry policies that apply to the brand, configures parameters where needed, and adds any custom policies specific to the brand. The buying team never interacts with this configuration — they create campaign plans that reference the brand, and the governance agent resolves applicable policies automatically. The brand’s industry verticals inform automatic policy matching — for example, a brand in the beverage vertical would receive any registry policies tagged for that vertical.

Policy registry

The policy registry is a community-maintained library of standardized, machine-readable advertising compliance policies. Brands reference policies by ID rather than writing their own. The registry covers three categories:

Category	Examples
Jurisdiction	UK HFSS restrictions, US COPPA, EU GDPR age-gating, California AI disclosure (SB 942)
Vertical	Alcohol age verification, pharma fair balance, gambling self-exclusion, financial services APR disclosure
Brand safety	Brand safety baselines, content suitability tiers

Each policy in the registry has an ID, applicable jurisdictions, a description, and machine-readable rules that governance agents can evaluate programmatically. Policies are versioned as regulations change; brand references MAY pin a specific version, and unversioned references resolve to the current version. The registry format and hosting mechanism are under development by the AgenticAdvertising.org Governance Working Group. This model follows the pattern established by IEEE 7012 (Machine Readable Personal Privacy Terms), which maintains a neutral roster of standardized agreements that parties reference rather than draft individually.

Policy resolution

Policies are declared directly on the plan via policy_ids and custom_policies. When a plan is synced, the governance agent resolves the active policy set:

Load registry policies referenced by policy_ids
Intersect with the plan’s countries and regions — only policies applicable to the plan’s markets are active
Include all custom_policies (these apply regardless of geography)

The plan’s countries and regions fields also serve as geo enforcement: the governance agent MUST reject media buys targeting markets outside the plan’s allowed geography. A plan with regions: ["US-MA"] rejects buys not explicitly targeting Massachusetts, even if they are otherwise compliant. These fields use the same ISO codes and semantics as product-filters, offerings, and create_media_buy. The resolved policy set is what the governance agent evaluates during check_governance. For the brand_policy and regulatory_compliance categories, the governance agent validates against this resolved set. If the plan has no policy_ids or custom_policies, the governance agent operates with an empty policy set for policy-based categories. Other categories (budget_authority, strategic_alignment, etc.) still apply based on the plan’s parameters.

State tracking

The governance agent tracks state at two levels:

Plan level: Total budget committed, channel allocation percentages, plan status
Campaign level: Per-buyer_campaign_ref committed budget, active media buy references, validation history

A single plan can span multiple campaigns. When check_governance checks budget authority, it considers all campaigns tied to the plan. When report_plan_outcome reports a seller confirmation, the governance agent commits the budget from the seller’s actual amount — not the requested amount.

Plan status

Status	Meaning
`active`	Accepting validation requests and outcome reports
`suspended`	Paused pending human review of a critical escalation
`completed`	Plan finished; read-only

When status is suspended, the governance agent MUST reject all check_governance and report_plan_outcome requests with a CAMPAIGN_SUSPENDED error until the escalation is resolved.

Budget tracking

Budget is committed based on confirmed outcomes, not validated actions. The flow:

check_governance with binding: "proposed" checks whether the proposed spend fits within the plan. No budget is committed yet.
The orchestrator executes the action with the seller.
report_plan_outcome reports the seller’s confirmed amount. The governance agent commits this amount to the plan budget.

This ensures budget tracking reflects reality. If a seller reduces the budget from

150K to

120K, the governance agent commits

120K and returns findings about the discrepancy. If the action fails entirely, the governance agent commits

0. A committed approval validates the seller’s planned delivery against the plan but does not commit budget. Budget is only committed when the orchestrator calls report_plan_outcome with the seller’s confirmed response. Budget checks are point-in-time: check_governance validates against the current committed total but does not reserve budget. If multiple agents execute concurrently against the same plan, two checks could both pass and the combined outcomes could exceed the authorized budget. The governance agent detects overspend at outcome reporting time and returns a budget_authority finding. To prevent concurrent overspend, use delegations with per-agent budget_limit to partition the budget across executing agents.

Drift detection

The audit log includes drift_metrics that surface aggregate governance trends over the plan’s lifetime:

{
  "summary": {
    "checks_performed": 847,
    "drift_metrics": {
      "escalation_rate": 0.03,
      "escalation_rate_trend": "declining",
      "auto_approval_rate": 0.91,
      "human_override_rate": 0.02,
      "mean_confidence": 0.88
    }
  }
}

These metrics detect oversight drift — the gradual migration of control away from humans. A declining escalation rate may indicate the governance agent is well-calibrated, or it may indicate that oversight is eroding. Surfacing the trend lets the organization make that judgment.

Metric	What it measures
`escalation_rate`	Fraction of checks that resulted in escalation
`escalation_rate_trend`	Direction over the plan’s lifetime (`increasing`, `stable`, `declining`)
`auto_approval_rate`	Fraction of checks approved without human intervention
`human_override_rate`	Fraction of escalations where the human overrode the governance agent
`mean_confidence`	Average confidence score across findings (when confidence is reported)

Organizations can set thresholds on drift metrics. When a metric crosses its threshold, the governance agent SHOULD include a finding (severity warning) on the next governance check:

{
  "drift_metrics": {
    "escalation_rate": 0.01,
    "escalation_rate_trend": "declining",
    "auto_approval_rate": 0.97,
    "thresholds": {
      "escalation_rate_min": 0.02,
      "auto_approval_rate_max": 0.95
    }
  }
}

In this example, both thresholds are breached — the escalation rate (0.01) is below the minimum (0.02) and the auto-approval rate (0.97) exceeds the maximum (0.95). This could indicate that the governance agent is approving too broadly, or that policies are well-calibrated for a low-risk campaign. The threshold breach surfaces the question; the organization decides the answer. Organizations set only the thresholds relevant to their concern. An escalation_rate_min catches oversight erosion; an escalation_rate_max catches policy miscalibration. A human_override_rate_max catches a governance agent whose recommendations are consistently wrong. All threshold fields are optional.

Plan amendments

Calling sync_plans with an existing plan_id updates the plan (upsert). The governance agent increments plan_version and applies the new parameters immediately. Active media buys that were approved under the previous plan version are not automatically re-validated — the governance agent evaluates them against the updated plan on the next check_governance call (e.g., the next delivery check). If an amendment reduces the budget below the currently committed amount, the governance agent flags this as a finding on the next governance check.

Validation logic

The governance agent evaluates each validation category independently:

If any category has status failed and the failure is correctable, the status is conditions with suggested fixes
If any category has status failed and the failure is not correctable by the caller, the status is denied
If all categories pass but the overall risk profile warrants human review, the status is escalated
If all categories pass, the status is approved

The conditions array is only present when the status is conditions. Each condition identifies a specific field, its current value, a suggested value, and the reason for the change.

Finding confidence

Governance findings include an optional confidence score (0-1) and uncertainty_reason that distinguish certain violations from ambiguous ones:

{
  "category_id": "regulatory_compliance",
  "severity": "critical",
  "confidence": 0.85,
  "uncertainty_reason": "Targeting includes 'New Mexico' which partially overlaps LATAM HFSS jurisdiction boundaries",
  "explanation": "Potential HFSS jurisdiction violation based on targeting geography."
}

Confidence informs the appropriate response:

High confidence (0.9+): The finding is definitive. A GDPR violation on a campaign explicitly targeting EU users.
Medium confidence (0.6-0.9): The finding depends on context the governance agent cannot fully resolve. Audience segments that may include minors, geo targeting that partially overlaps regulated jurisdictions.
Low confidence (below 0.6): The finding is speculative. The governance agent flags it for human review rather than acting on it autonomously.

Without confidence, every finding is presented as equally certain, which either over-blocks (if treated as certain) or trains people to ignore findings (if many are false positives). Governance agents SHOULD include confidence when the evaluation involves natural language interpretation or probabilistic matching.

Phase inference

The governance agent infers the validation phase from the tool parameter in check_governance:

tool	Phase
`get_products`	Discovery — validates search intent, seller eligibility, product suitability
`create_media_buy`	Purchase — validates budget authority, targeting compliance, flight dates
`update_media_buy`	Purchase — validates change magnitude, reallocation thresholds

Phase context is cumulative. During purchase, the governance agent considers what was discovered during discovery. The check_id returned by check_governance is used by report_plan_outcome to link the seller’s response back to the validated action.

Capability declaration

Governance agents declare their Campaign Governance support in get_adcp_capabilities:

{
  "governance": {
    "campaign_governance": {
      "categories": [
        {
          "category_id": "budget_authority",
          "description": "Validates spend against plan budget limits and allocation rules."
        },
        {
          "category_id": "strategic_alignment",
          "description": "Validates that purchases match campaign brief and channel mix targets."
        },
        {
          "category_id": "bias_fairness",
          "description": "Checks targeting for discriminatory patterns and protected category compliance.",
          "jurisdictions": ["US", "EU", "UK"]
        },
        {
          "category_id": "regulatory_compliance",
          "description": "Validates jurisdiction-specific advertising regulations.",
          "jurisdictions": ["US", "EU", "UK"]
        },
        {
          "category_id": "seller_verification",
          "description": "Compares seller setup against original requests to detect discrepancies."
        },
        {
          "category_id": "brand_policy",
          "description": "Enforces brand-level compliance policies resolved from the brand configuration and policy registry."
        }
      ]
    }
  }
}

Integration with `create_media_buy`

The buyer includes plan_id and buyer_campaign_ref as first-class fields on the create_media_buy request. These fields tell the seller which governance plan applies, enabling seller-side governance checks.

{
  "tool": "create_media_buy",
  "arguments": {
    "buyer_ref": "q1-launch-pinnacle-001",
    "buyer_campaign_ref": "q1-2026-spring-launch",
    "plan_id": "plan_q1_2026_launch",
    "account": { "agent_url": "https://seller.example.com", "id": "acc_123" },
    "brand": { "domain": "acmecorp.com" },
    "start_time": "2026-03-15T00:00:00Z",
    "end_time": "2026-06-15T00:00:00Z",
    "packages": ["..."]
  }
}

The seller’s response includes planned_delivery — what the seller will actually run:

{
  "media_buy_id": "mb_seller_456",
  "buyer_ref": "q1-launch-pinnacle-001",
  "buyer_campaign_ref": "q1-2026-spring-launch",
  "packages": ["..."],
  "planned_delivery": {
    "geo": { "countries": ["US"] },
    "channels": ["olv"],
    "start_time": "2026-03-15T00:00:00Z",
    "end_time": "2026-06-15T00:00:00Z",
    "total_budget": 150000,
    "currency": "USD",
    "frequency_cap": { "max_impressions": 3, "per": "user", "window": { "interval": 1, "unit": "days" } },
    "audience_summary": "Adults 25-54, US, premium video inventory",
    "enforced_policies": ["us_coppa"]
  }
}

planned_delivery is the seller’s interpretation of the request — the actual delivery parameters they will use. It serves two purposes:

Governance checks — When the account has governance_agents, the seller sends planned_delivery to the governance agent(s) for verification before confirming the media buy.
Transparency — The buyer can compare planned_delivery against what they requested to catch discrepancies early, before delivery begins.

Governance checks

Campaign Governance’s buyer-side validation has a trust limitation: the buyer’s orchestrator grades its own homework. An LLM agent could hallucinate governance approval, skip validation, or misrepresent what was validated. Seller-side governance checks close this gap by giving sellers an independent way to confirm that purchases are approved. The seller POSTs to the buyer’s governance_agents URLs when media buy events occur. The governance agent maintains all state and correlates requests by plan_id + media_buy_id — the seller does not need to track governance history or chain IDs across calls.

Setup

The buyer registers governance_agents when syncing accounts with the seller. Each agent includes authentication credentials so the governance agent can verify the seller’s identity:

{
  "tool": "sync_accounts",
  "arguments": {
    "accounts": [
      {
        "brand": { "domain": "acmecorp.com" },
        "operator": "pinnacle-media.com",
        "billing": "operator",
        "governance_agents": [
          {
            "url": "https://governance.pinnacle-media.com",
            "authentication": {
              "schemes": ["Bearer"],
              "credentials": "gov_token_acme_pinnacle_2026_xyz..."
            }
          }
        ]
      }
    ]
  }
}

The seller stores these endpoints and presents the credentials when calling check_governance. The governance agent MUST verify that the Bearer token matches a registered credential for the account associated with the plan_id, and MUST reject requests with unrecognized or mismatched credentials.

Governance modes

The governance agent’s operating mode can be set per-plan via the mode field in sync_plans, defaulting to enforce. Mode is not exposed to sellers via sync_accounts — the seller calls check_governance and acts on the response status. It does not need to know whether the governance agent is in audit, advisory, or enforce mode. This avoids requiring account re-syncs when the mode changes and prevents sellers from adjusting behavior based on mode.

Mode	Behavior	Use case
`audit`	Log all checks. Never block — always return `approved`, with findings attached for review.	Initial rollout. See what governance would flag without disrupting live campaigns.
`advisory`	Return findings with real statuses (`denied`, `conditions`, `escalated`), but do not block execution.	Post-hoc human review. The governance agent expresses opinions; humans act on them.
`enforce`	Block on `denied` or `escalated`. Require resolution before proceeding.	Production governance. The default.

Default is enforce. Organizations can start in audit mode to build confidence in the governance agent’s calibration before enabling enforcement. In audit mode, the governance agent still performs full evaluation and returns findings — the only difference is that the status is always approved. This produces a complete audit trail that the organization can review to assess false positive rates and calibrate policies before going live. In advisory mode, the governance agent returns the real status it would have returned under enforcement. The check response includes a mode field so auditors can distinguish “denied in advisory mode (action proceeded)” from “denied in enforce mode (action blocked).” In all modes, delegation violations, credential mismatches, and other authorization checks are logged as findings. In audit and advisory modes, these findings do not block the action — they are recorded for review. Only in enforce mode are authorization violations blocking.

Governance context

The payload field in check_governance is opaque — it carries the full tool arguments for whatever tool is being checked. Different tools use different field names and structures for the same concepts (budget, countries, channels, flight dates). Without a standard extraction point, every governance agent must implement multi-format heuristics to find these values. The optional governance_context field solves this by providing a canonical shape for governance-relevant fields. The caller (orchestrator or seller) extracts budget, countries, channels, and flight dates from the tool payload into governance_context before calling check_governance. The governance agent validates against this known structure instead of parsing the payload directly. When governance_context is present, the governance agent SHOULD use it for plan validation. When absent, the agent falls back to inspecting payload. Callers SHOULD include governance_context for proposed checks where the payload structure varies by tool. For committed checks, planned_delivery already provides a canonical structure and governance_context is not needed. The governance_context condition field paths use the prefix governance_context. (e.g., governance_context.total_budget.amount) so they remain stable regardless of the original payload structure.

Governance phases

Governance checks cover the full media buy lifecycle through three phases:

Phase	Trigger	What’s validated
`purchase`	`create_media_buy`	Budget, geo, channels, flight dates, policies
`modification`	`update_media_buy`	Change magnitude, reallocation, new parameters
`delivery`	Periodic (seller-initiated)	Pacing, spend rate, geo drift, channel distribution

The phase field defaults to purchase if omitted, so existing implementations continue to work without changes. The governance agent maintains all state and correlates requests by plan_id + media_buy_id. The seller does not chain check IDs or track conversation history — it posts what happened, and the governance agent looks up context.

Purchase phase

When the seller receives a create_media_buy request on an account with governance_agents:

The seller interprets the request and determines its planned_delivery.
The seller calls check_governance with phase: "purchase", the plan_id, and planned_delivery.
The governance agent validates the planned delivery against the campaign plan.
If approved, the seller confirms the media buy.
If denied, the seller rejects the media buy with an GOVERNANCE_DENIED error.
If conditions, the seller adjusts its planned delivery to meet the conditions and re-verifies, or rejects.

Modification phase

When the seller receives an update_media_buy request:

The seller interprets the update and determines the new planned_delivery.
The seller calls check_governance with phase: "modification", the updated planned_delivery, and a modification_summary.
The governance agent looks up the media buy by plan_id + media_buy_id and evaluates the changes against the plan.
If approved, the seller confirms the update.
If denied or conditions, the seller follows the same flow as purchase phase.

The governance agent can apply different logic to modifications than to initial purchases. For example, a small budget increase within reallocation_threshold might be auto-approved, while a large budget increase or new geo market might require stricter scrutiny.

Delivery phase

The seller calls check_governance with phase: "delivery" periodically during active delivery. This creates a direct reporting channel between the seller and the buyer’s governance agent.

The seller collects delivery metrics for the reporting period.
The seller calls check_governance with phase: "delivery", the current planned_delivery, and delivery_metrics.
If approved, the response includes next_check — when the seller should report again.
If denied, the seller pauses delivery immediately.
If conditions, the seller adjusts delivery (e.g., slow pacing, shift geo targeting) and re-verifies immediately.

The governance agent opts in to delivery reporting by including next_check in the purchase approval response. If the purchase response has no next_check, the governance agent does not expect delivery reports. The governance agent controls the reporting cadence through next_check. It can tighten the cadence (shorter intervals) when it detects drift or conditions, and relax it (longer intervals) when delivery is stable. The governance agent MAY treat a missed next_check deadline as a finding on the next delivery check.

Verification examples

Purchase request:

{
  "tool": "check_governance",
  "arguments": {
    "plan_id": "plan_q1_2026_launch",
    "buyer_campaign_ref": "q1-2026-spring-launch",
    "binding": "committed",
    "caller": "https://seller.example.com",
    "media_buy_id": "mb_seller_456",
    "buyer_ref": "q1-launch-pinnacle-001",
    "phase": "purchase",
    "planned_delivery": {
      "geo": { "countries": ["US"] },
      "channels": ["olv"],
      "start_time": "2026-03-15T00:00:00Z",
      "end_time": "2026-06-15T00:00:00Z",
      "total_budget": 150000,
      "currency": "USD",
      "frequency_cap": { "max_impressions": 3, "per": "user", "window": { "interval": 1, "unit": "days" } },
      "audience_summary": "Adults 25-54, US, premium video inventory",
      "enforced_policies": ["us_coppa"]
    }
  }
}

Authorized (purchase with delivery opt-in):

{
  "check_id": "auth_001",
  "status": "approved",
  "binding": "committed",
  "plan_id": "plan_q1_2026_launch",
  "buyer_campaign_ref": "q1-2026-spring-launch",
  "explanation": "Planned delivery is within plan parameters. Budget: $150,000 of $500,000 plan total. Geo: US (within plan). Channel: OLV (within 40-70% target range).",
  "expires_at": "2026-03-15T01:00:00Z",
  "next_check": "2026-03-22T00:00:00Z"
}

The next_check field signals that the governance agent expects delivery reporting. If absent, no delivery reports are expected. Denied (purchase):

{
  "check_id": "auth_002",
  "status": "denied",
  "binding": "committed",
  "plan_id": "plan_q1_2026_launch",
  "buyer_campaign_ref": "q1-2026-spring-launch",
  "explanation": "Planned delivery targets CA (Canada) which is not an authorized market for this plan.",
  "findings": [
    {
      "category_id": "strategic_alignment",
      "severity": "critical",
      "explanation": "Geo targeting includes CA but plan only authorizes US.",
      "details": {
        "plan_countries": ["US"],
        "planned_countries": ["US", "CA"]
      }
    }
  ]
}

Authorized (delivery):

{
  "check_id": "auth_004",
  "status": "approved",
  "binding": "committed",
  "plan_id": "plan_q1_2026_launch",
  "buyer_campaign_ref": "q1-2026-spring-launch",
  "explanation": "Delivery on track. Week 1 spend: $12,500 of $150,000 (8.3%). Pacing is on target for 13-week flight.",
  "next_check": "2026-03-29T00:00:00Z"
}

Enforcement

When governance_agents is present on the account, the seller MUST call check_governance before confirming any media buy. The buyer provided the endpoints specifically so that purchases are independently verified — skipping it defeats the purpose. When governance_agents is absent, the seller processes media buy requests normally. The buyer-side governance loop (check_governance(binding: proposed) -> execute -> report_plan_outcome) still applies, but there is no seller-side verification. Sellers MUST NOT require governance checks as a prerequisite for all accounts. A seller that refuses to process media buys from accounts without governance_agents would break interoperability with buyers who do not use Campaign Governance. The delivery phase is optional even when purchase phase governance is used. A seller MAY support purchase approval without ongoing delivery reporting. The governance agent indicates whether it expects delivery reports through the presence of next_check in the purchase response. If the governance agent is unreachable (timeout, network error), the seller MUST NOT proceed with the media buy. Governance checks are a prerequisite for confirming purchases on accounts with registered governance_agents. The seller SHOULD retry the check after a brief delay and reject the media buy with a GOVERNANCE_UNAVAILABLE error if the agent remains unreachable. When the orchestrator receives GOVERNANCE_UNAVAILABLE from a seller, it SHOULD retry the create_media_buy after a delay. If the governance agent remains unavailable, the orchestrator SHOULD escalate to a human rather than attempting alternative sellers — the governance outage affects all sellers on the same account. A prior proposed approval from the orchestrator does not substitute for the seller’s committed check; the seller validates independently and cannot use the orchestrator’s approval.

Performance expectations

Governance agent implementations SHOULD respond to check_governance calls within 5 seconds for proposed checks and 10 seconds for committed checks. Sellers SHOULD configure appropriate timeouts and treat timeouts the same as unavailability (retry, then reject with GOVERNANCE_UNAVAILABLE).

Wire format

The seller calls each governance agent at its registered URL using MCP over HTTP (Streamable HTTP transport). The request is an MCP tools/call invocation with tool name check_governance and the request arguments as the tool input. Authentication uses the Bearer token from the agent’s authentication.credentials in the Authorization header.

Multi-agent composition

Accounts MAY register multiple governance agents via the governance_agents array on sync_accounts, each responsible for different validation categories. For example, one agent handles budget authority and strategic alignment while another handles regulatory compliance and brand policy. When multiple governance agents are registered, the seller MUST call each agent whose categories overlap with the action being validated. All applicable agents must approve for the action to proceed (unanimous approval). If any agent returns denied or escalated, the action is blocked. For accounts with a single governance agent, pass a one-element array.

Governance checks and the governance loop

Governance checks complement the buyer-side governance loop, they do not replace it:

Concern	Buyer-side (`check_governance`, `binding: "proposed"`)	Seller-side (`check_governance`, `binding: "committed"`)
Who checks	Buyer’s governance agent, called by orchestrator	Buyer’s governance agent, called by seller
When	Before the buyer sends the request	Before confirm, on update, during delivery
What’s validated	The buyer’s intended action	The seller’s planned and actual delivery
Trust model	Self-attested	Independently verified
Budget tracking	Yes (plan state)	Governance agent maintains state
Ongoing monitoring	Via `report_plan_outcome`	Via `delivery` phase

The delivery phase gives the governance agent real-time visibility into what sellers are actually delivering. The buyer-side report_plan_outcome depends on the orchestrator reporting honestly; the delivery phase gets reports directly from the seller. The buyer-side and seller-side governance checks MAY be handled by the same agent or by separate agents. The protocol does not prescribe the relationship — only that the seller can call the governance_agents URLs registered on the account.

Orchestrator integration pattern

The governance check is a synchronous call in the orchestrator’s action loop. The orchestrator calls check_governance with binding: "proposed" before sending requests to sellers. Seller-side governance checks use binding: "committed" and are transparent to the orchestrator — the orchestrator sends the same create_media_buy request regardless of whether governance checks are configured. Modification and delivery phase checks happen between the seller and governance agent, independent of the orchestrator’s governance loop.

Audit trail

Every plan maintains an ordered audit trail of all validated actions and reported outcomes, retrievable via get_plan_audit_logs. The trail includes:

Check ID, timestamp, and tool
The status and category evaluations
Outcome status and committed budget
Any findings from outcome reports
Any escalations and their resolutions
The human approver identity (when escalated)
Delivery metrics over time

This audit trail serves compliance and reporting needs. For regulated categories (political advertising, financial services), the trail provides evidence that governance was applied to every transaction.

Conformance testing

A conformance test suite for governance agent implementations is planned. Test vectors provide structured input/output pairs — a plan, a set of policies, a check_governance request, and the expected response status and findings. Governance agents can run these vectors to verify that their policy evaluation produces consistent results. The policy registry’s exemplars (pass/fail scenarios per policy) provide the raw material. Test vectors formalize these into executable assertions that any governance agent can validate against. The AdCP client test library will include these vectors as part of its standard test suite.

Property list governance

Campaign governance intersects with property governance when media buys reference property lists. A governance agent MAY validate that property lists referenced in media buy requests meet the plan’s brand safety and compliance requirements, ensuring that property lists align with the brand’s compliance configuration and enforced policies.

​Campaign Governance specification

​Campaign plan

​Budget authority levels

​Channel mix targets

​Delegations

​Portfolio governance

​Brand compliance configuration

​Policy registry

​Policy resolution

​State tracking

​Plan status

​Budget tracking

​Drift detection

​Plan amendments

​Validation logic

​Finding confidence

​Phase inference

​Capability declaration

​Integration with create_media_buy

​Governance checks

​Setup

​Governance modes

​Governance context

​Governance phases

​Purchase phase

​Modification phase

​Delivery phase

​Verification examples

​Enforcement

​Performance expectations

​Wire format

​Multi-agent composition

​Governance checks and the governance loop

​Orchestrator integration pattern

​Audit trail

​Conformance testing

​Property list governance

Campaign Governance specification

Campaign plan

Budget authority levels

Channel mix targets

Delegations

Portfolio governance

Brand compliance configuration

Policy registry

Policy resolution

State tracking

Plan status

Budget tracking

Drift detection

Plan amendments

Validation logic

Finding confidence

Phase inference

Capability declaration

Integration with `create_media_buy`

Governance checks

Setup

Governance modes

Governance context

Governance phases

Purchase phase

Modification phase

Delivery phase

Verification examples

Enforcement

Performance expectations

Wire format

Multi-agent composition

Governance checks and the governance loop

Orchestrator integration pattern

Audit trail

Conformance testing

Property list governance