Adform Channel Conflict Audit

Adform direct-versus-RTB channel conflict audit

Compares the targeting of direct and RTB line items under a campaign to surface overlap on the same domains, audiences, or placements where both types are delivering simultaneously. Read-only.

Connection & tooling

Runs on the Adform GraphQL MCP. Use graphql_execute to run queries. Use graphql_introspect on RtbLineItemAudience and DirectLineItem to discover targeting field shapes. Keep calls sequential (~1–2s apart).

---

Step 1 — List RTB line items under the order

{
  rtbLineItems(
    orderIds: ["67890"]
    offset: 0
    limit: 20
  ) {
    lineItems { id name environments orderId campaignId paused }
    totalCount
  }
}

Step 2 — List direct line items under the order

{
  directLineItems(
    orderId: "67890"
    pagination: { offset: 0, limit: 20 }
  ) {
    directLineItems { id name status }
    totalCount
  }
}

Step 3 — Get targeting detail for each

For RTB line items, use graphql_introspect on RtbLineItemAudience to select targeting rules including domains, audience segments, and locations:

The id is the RTB setup ID returned by rtbLineItems(), not the placement ID.

{ rtbLineItem(id: "99999") { id targetings { id name bidMultiplier } inventories { id buyingType } } }

Resolve domain targeting list IDs to actual domains:

{ rtbTargetingListDomains(id: "12345", pagination: { offset: 0, limit: 100 }) { domains { name bidMultiplier } totalCount } }

Step 4 — Delivery confirmation

Only flag as a conflict when both sides are actively delivering in the same time window. Check delivery indications for each line item:

{ rtbLineItemDeliveryIndications(id: "99999") { status effectiveFlightDailyCost } }

Step 5 — Quantify conflict with mcpStats domain breakdown

Step 4 confirms both sides are live. Use mcpStats to pull actual impression volume by domain for the RTB line item to measure how much inventory is being won on the conflicting domains. Validated query:

{
  mcpStats {
    totalRowCount
    totals
    columns {
      dimensions { rtbDomain { name } }
      metrics {
        impressions
        clicks
        cost
        ecpm
        rtbBids
        rtbWinRate
      }
    }
    rows(
      filter: {
        date: { from: "2026-06-01", to: "2026-06-30" }
        advertiser: { ids: ["2133936"] }
      }
      paging: { offset: 0, limit: 100 }
      sort: [{ column: 1, direction: desc }]
    )
  }
}

Filter the result client-side to only the domains identified as overlapping in Step 3. The impression volume on those domains is the quantity of inventory where self-competition is occurring. Include this in the conflict table as "impressions at risk" alongside the cost figure to communicate business impact.

---

Method

1. Gather direct and RTB line items under the order; retain only those currently delivering
2. Compare targeting: shared domains (resolve both lists), overlapping audience segment IDs,

overlapping placements

1. Flag only intersections where both sides show active delivery — that is the real conflict

Presenting

Conflict table: the direct line item, the RTB line item, the overlap dimension (domains, audience, or placement), whether both are currently live, impressions at risk (from mcpStats domain breakdown), and cost at risk. Lead with overlaps where both sides are delivering. Quantify the scale of self-competition using the mcpStats impression count on conflicting domains. Recommend de-duplicating targeting to eliminate self-competition.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: adform
• Source: adform/agentic-skills
• License: MIT
• Homepage: https://site.adform.com

Install and usage instructions live in the source repository linked above.