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The examples below start with what a human says, then show the structured request_proposals request an agent should send. The goal is not to make the brief verbose. Preserve campaign meaning in prose and move exact values into typed fields.

Local service launch

Human request

Help Acme Home Services drive appointment calls from homeowners in Colorado during October. We have $8,000 and only want display inventory priced in USD.

AdCP request

The seller interprets “homeowners” and contextual fit. It does not infer the state, channel, currency, dates, or budget.

Multi-country B2B campaign

Human request

Pinnacle Cloud wants qualified leads from technical leaders at growing businesses in the US, Canada, UK, and Germany. We need display or online video, USD or EUR pricing, and completed-view reporting where video is used.

AdCP request

The brief carries job-function meaning because AdCP does not impose one global taxonomy for “technical leader.” Geography and product requirements are exact.

Known country, cities selected later

Human request

Nova Meals is launching nationally to parents ages 25–44. After we compare forecasts, our planners will choose separate DMAs and placements for each package. We do not want one product returned per city.

AdCP request

targeting_overlay is applied now and participates in every returned forecast. required_overlay_support filters to products that let packages select DMAs and placements later. It does not create a product or package per value.

Hard prose fallback

Structured-first authoring is a SHOULD, not permission for sellers to ignore prose. If a buyer sends:
the seller still applies the hard constraints and, because they affect product eligibility, pricing, and forecasting, must confirm the structured interpretation in targeting_resolution.brief_targeting. The buyer should not infer confirmation from a missing resolution. Legacy callers can express the same decomposition through get_products with buying_mode: "brief", top-level filters, targeting_overlay, and required_overlay_support. The split tasks are preferred because they make the listing, proposal, and refinement lifecycle explicit.

Practice

Decompose this request before revealing the answer:
Acme Audio has $75,000 for a six-week US podcast launch. Only USD pricing. We need completion reporting, want music and technology enthusiasts, and will choose individual shows after reviewing the publisher’s recommendations.
  • Brief: launch context plus music and technology enthusiast intent.
  • Offer filters: podcast channel, USD currency, six-week dates, $75,000 budget, and required completion metric.
  • Targeting overlay: US.
  • Required overlay support: placement or collection selection later, depending on how the seller models public shows.

Review every response

Before purchase:
  1. Confirm offer filters excluded ineligible offers.
  2. Confirm forecast and price reflect the structured overlay.
  3. Verify overlay_support covers every later-selectable requirement.
  4. Review targeting_resolution.modifications and any brief_targeting.
  5. Accept a configured product only when its complete targeting resolution is acceptable.