|
| 1 | +id: signal_marketplace |
| 2 | +version: "1.0.0" |
| 3 | +title: "Marketplace signal agent" |
| 4 | +category: signal_marketplace |
| 5 | +summary: "Signal agent that resells third-party data provider signals with verifiable catalog provenance." |
| 6 | + |
| 7 | +narrative: | |
| 8 | + You operate a signal marketplace — an intermediary that aggregates audience data from |
| 9 | + multiple third-party providers and makes it available to buyers through a single interface. |
| 10 | + Think LiveRamp Data Marketplace, Oracle Data Cloud, or Lotame. |
| 11 | +
|
| 12 | + Your agent searches across catalogs published by data providers in their adagents.json |
| 13 | + files. Buyers discover signals through natural language queries, verify provenance by |
| 14 | + checking the data provider's catalog directly, and activate signals on DSPs or sales |
| 15 | + agents for campaign targeting. |
| 16 | +
|
| 17 | + The key property of marketplace signals: provenance is independently verifiable. Each |
| 18 | + signal traces back to a data_provider_domain whose adagents.json lists your agent as |
| 19 | + authorized. Buyers can (and should) verify this before spending. |
| 20 | +
|
| 21 | + This storyboard walks through discovery, verification, and both activation patterns — |
| 22 | + activating directly on a DSP (buyer manages targeting) and activating on a sales agent |
| 23 | + (SA handles downstream coordination). |
| 24 | +
|
| 25 | +agent: |
| 26 | + interaction_model: marketplace_catalog |
| 27 | + capabilities: |
| 28 | + - catalog_signals |
| 29 | + examples: |
| 30 | + - "LiveRamp Data Marketplace" |
| 31 | + - "Oracle Data Cloud" |
| 32 | + - "Lotame" |
| 33 | + |
| 34 | +caller: |
| 35 | + role: buyer_agent |
| 36 | + example: "Pinnacle Agency (buyer)" |
| 37 | + |
| 38 | +prerequisites: |
| 39 | + description: | |
| 40 | + The buyer has a campaign brief with targeting objectives. The test kit provides |
| 41 | + sample signal definitions, pricing options, and destination configurations that |
| 42 | + match the training agent's signal providers. |
| 43 | + test_kit: "test-kits/nova-motors.yaml" |
| 44 | + |
| 45 | +phases: |
| 46 | + - id: discovery |
| 47 | + title: "Signal discovery" |
| 48 | + narrative: | |
| 49 | + The buyer describes what they need in natural language. Your agent searches |
| 50 | + across all authorized data provider catalogs and returns matching signals with |
| 51 | + pricing, coverage estimates, and value types. |
| 52 | +
|
| 53 | + This is where marketplace agents earn their keep — the buyer doesn't need to |
| 54 | + know which providers exist or what taxonomies they use. One query, many sources. |
| 55 | +
|
| 56 | + steps: |
| 57 | + - id: search_by_spec |
| 58 | + title: "Discover signals from a campaign brief" |
| 59 | + narrative: | |
| 60 | + The buyer's platform translates a campaign brief into a get_signals call. |
| 61 | + Your agent searches catalogs from every authorized data provider and returns |
| 62 | + what matches — automotive intent from one provider, geo data from another, |
| 63 | + retail purchase history from a third. |
| 64 | + task: get_signals |
| 65 | + schema_ref: "signals/get-signals-request.json" |
| 66 | + response_schema_ref: "signals/get-signals-response.json" |
| 67 | + doc_ref: "/signals/tasks/get_signals" |
| 68 | + stateful: false |
| 69 | + expected: | |
| 70 | + Return matching signals from multiple data providers. Each signal must include: |
| 71 | + - signal_agent_segment_id for activation |
| 72 | + - signal_id with source, data_provider_domain, and id |
| 73 | + - name, description, and value_type (binary, categorical, or numeric) |
| 74 | + - coverage_percentage (audience reach estimate) |
| 75 | + - pricing_options with at least one pricing model |
| 76 | + - signal_type: "marketplace" |
| 77 | +
|
| 78 | + sample_request: |
| 79 | + signal_spec: "In-market EV buyers with high purchase propensity, near auto dealerships" |
| 80 | + |
| 81 | + validations: |
| 82 | + - check: response_schema |
| 83 | + description: "Response matches get-signals-response.json schema" |
| 84 | + - check: field_present |
| 85 | + path: "signals[0].signal_agent_segment_id" |
| 86 | + description: "Each signal has a signal_agent_segment_id" |
| 87 | + - check: field_present |
| 88 | + path: "signals[0].signal_id.data_provider_domain" |
| 89 | + description: "Each signal traces to a data provider domain" |
| 90 | + - check: field_present |
| 91 | + path: "signals[0].pricing_options" |
| 92 | + description: "Each signal has pricing options" |
| 93 | + - check: field_present |
| 94 | + path: "signals[0].coverage_percentage" |
| 95 | + description: "Each signal has a coverage estimate" |
| 96 | + |
| 97 | + - id: search_by_ids |
| 98 | + title: "Look up specific signals by ID" |
| 99 | + narrative: | |
| 100 | + The buyer already knows which signals they want — maybe from a previous |
| 101 | + campaign or a provider's documentation. They pass signal_ids directly |
| 102 | + instead of a natural language query. |
| 103 | + task: get_signals |
| 104 | + schema_ref: "signals/get-signals-request.json" |
| 105 | + response_schema_ref: "signals/get-signals-response.json" |
| 106 | + doc_ref: "/signals/tasks/get_signals" |
| 107 | + stateful: false |
| 108 | + expected: | |
| 109 | + Return the exact signals requested, with full metadata and pricing. |
| 110 | + If a signal_id doesn't exist, omit it from results — don't error. |
| 111 | +
|
| 112 | + sample_request: |
| 113 | + signal_ids: |
| 114 | + - source: "catalog" |
| 115 | + data_provider_domain: "tridentauto.example" |
| 116 | + id: "likely_ev_buyers" |
| 117 | + - source: "catalog" |
| 118 | + data_provider_domain: "meridiangeo.example" |
| 119 | + id: "competitor_visitors" |
| 120 | + |
| 121 | + validations: |
| 122 | + - check: response_schema |
| 123 | + description: "Response matches schema" |
| 124 | + - check: field_present |
| 125 | + path: "signals" |
| 126 | + description: "Response contains a signals array" |
| 127 | + |
| 128 | + - id: verification |
| 129 | + title: "Catalog verification" |
| 130 | + narrative: | |
| 131 | + Before activating third-party data, the buyer verifies provenance. They fetch |
| 132 | + the data provider's adagents.json directly and confirm the signal exists and |
| 133 | + your agent is authorized. This independent check is outside the AdCP protocol — |
| 134 | + but your agent must return the metadata that makes it possible. |
| 135 | +
|
| 136 | + This phase tests that your get_signals responses include verifiable provenance |
| 137 | + data: signal_id.source is "catalog" and signal_id.data_provider_domain points |
| 138 | + to a real domain whose adagents.json the buyer can fetch independently. |
| 139 | +
|
| 140 | + steps: |
| 141 | + - id: verify_provenance_metadata |
| 142 | + title: "Confirm signals carry verifiable provenance" |
| 143 | + narrative: | |
| 144 | + The buyer looks up a specific signal by ID and checks that the response |
| 145 | + includes the metadata needed for independent verification — source is |
| 146 | + "catalog" and data_provider_domain points to a fetchable adagents.json. |
| 147 | + The actual HTTP fetch of adagents.json is the buyer's responsibility, but |
| 148 | + your agent must provide the domain to fetch from. |
| 149 | + task: get_signals |
| 150 | + schema_ref: "signals/get-signals-request.json" |
| 151 | + response_schema_ref: "signals/get-signals-response.json" |
| 152 | + doc_ref: "/signals/data-providers" |
| 153 | + stateful: false |
| 154 | + expected: | |
| 155 | + Return the requested signal with verifiable provenance metadata: |
| 156 | + - signal_id.source is "catalog" |
| 157 | + - signal_id.data_provider_domain matches a real domain |
| 158 | + The buyer will independently fetch that domain's adagents.json to confirm |
| 159 | + your agent is listed in authorized_agents. |
| 160 | +
|
| 161 | + sample_request: |
| 162 | + signal_ids: |
| 163 | + - source: "catalog" |
| 164 | + data_provider_domain: "shopgrid.example" |
| 165 | + id: "new_to_brand" |
| 166 | + |
| 167 | + validations: |
| 168 | + - check: field_value |
| 169 | + path: "signals[0].signal_id.source" |
| 170 | + description: "Signal source is 'catalog' (verifiable via adagents.json)" |
| 171 | + - check: field_present |
| 172 | + path: "signals[0].signal_id.data_provider_domain" |
| 173 | + description: "Data provider domain is present for independent verification" |
| 174 | + |
| 175 | + - id: platform_activation |
| 176 | + title: "Activate on a DSP" |
| 177 | + narrative: | |
| 178 | + The buyer activates a signal directly on a DSP platform. The signal agent pushes |
| 179 | + segment data to the platform, and the buyer gets back a segment_id they can |
| 180 | + reference when configuring campaign targeting. |
| 181 | +
|
| 182 | + Use platform destinations when the buyer is managing DSP campaigns directly — |
| 183 | + not through a sales agent. |
| 184 | +
|
| 185 | + steps: |
| 186 | + - id: activate_on_platform |
| 187 | + title: "Activate signal on a DSP" |
| 188 | + narrative: | |
| 189 | + The buyer selects a signal and a DSP destination. The signal agent pushes |
| 190 | + the segment to the platform. This is typically asynchronous — the initial |
| 191 | + response shows is_live: false with an estimated duration, and the buyer |
| 192 | + polls for completion. |
| 193 | + task: activate_signal |
| 194 | + schema_ref: "signals/activate-signal-request.json" |
| 195 | + response_schema_ref: "signals/activate-signal-response.json" |
| 196 | + doc_ref: "/signals/tasks/activate_signal" |
| 197 | + stateful: true |
| 198 | + expected: | |
| 199 | + Return a deployment with: |
| 200 | + - type: "platform" matching the requested destination |
| 201 | + - is_live: false initially (async activation) |
| 202 | + - estimated_activation_duration_minutes |
| 203 | + After polling, the deployment should show: |
| 204 | + - is_live: true |
| 205 | + - activation_key with type: "segment_id" and a platform-native segment ID |
| 206 | + - deployed_at timestamp |
| 207 | +
|
| 208 | + sample_request: |
| 209 | + signal_agent_segment_id: "trident_likely_ev_buyers" |
| 210 | + pricing_option_id: "po_trident_ev_cpm" |
| 211 | + destinations: |
| 212 | + - type: "platform" |
| 213 | + platform: "the-trade-desk" |
| 214 | + account: "agency-123-ttd" |
| 215 | + |
| 216 | + validations: |
| 217 | + - check: response_schema |
| 218 | + description: "Response matches activate-signal-response.json schema" |
| 219 | + - check: field_present |
| 220 | + path: "deployments[0].type" |
| 221 | + description: "Deployment includes type" |
| 222 | + - check: field_value |
| 223 | + path: "deployments[0].type" |
| 224 | + description: "Deployment type is 'platform'" |
| 225 | + |
| 226 | + - id: agent_activation |
| 227 | + title: "Activate on a sales agent" |
| 228 | + narrative: | |
| 229 | + The buyer activates a signal on a sales agent instead of a DSP. This is the |
| 230 | + right pattern when the buyer is purchasing media through the SA — the SA handles |
| 231 | + its own DSP coordination. |
| 232 | +
|
| 233 | + The buyer doesn't need to know which DSP the SA uses. The activation key confirms |
| 234 | + the signal is live on the SA, and the SA applies targeting when fulfilling media |
| 235 | + buys through create_media_buy. |
| 236 | +
|
| 237 | + steps: |
| 238 | + - id: activate_on_agent |
| 239 | + title: "Activate signal on a sales agent" |
| 240 | + narrative: | |
| 241 | + The buyer activates a signal with the sales agent's URL as the destination. |
| 242 | + Agent activations are typically synchronous — the SA records the activation |
| 243 | + immediately and returns a key_value activation key. |
| 244 | + task: activate_signal |
| 245 | + schema_ref: "signals/activate-signal-request.json" |
| 246 | + response_schema_ref: "signals/activate-signal-response.json" |
| 247 | + doc_ref: "/signals/tasks/activate_signal" |
| 248 | + stateful: true |
| 249 | + expected: | |
| 250 | + Return a deployment with: |
| 251 | + - type: "agent" matching the requested destination |
| 252 | + - agent_url matching the SA's URL |
| 253 | + - is_live: true (sync activation) |
| 254 | + - activation_key with type: "key_value" |
| 255 | + - deployed_at timestamp |
| 256 | +
|
| 257 | + The SA records the activation internally. When the buyer later calls |
| 258 | + create_media_buy through this SA, signal-based targeting is already |
| 259 | + in place. |
| 260 | +
|
| 261 | + sample_request: |
| 262 | + signal_agent_segment_id: "shopgrid_new_to_brand" |
| 263 | + pricing_option_id: "po_shopgrid_retail_cpm" |
| 264 | + destinations: |
| 265 | + - type: "agent" |
| 266 | + agent_url: "https://wonderstruck.salesagents.example" |
| 267 | + |
| 268 | + validations: |
| 269 | + - check: response_schema |
| 270 | + description: "Response matches activate-signal-response.json schema" |
| 271 | + - check: field_present |
| 272 | + path: "deployments[0].activation_key" |
| 273 | + description: "Deployment includes activation key" |
| 274 | + - check: field_value |
| 275 | + path: "deployments[0].type" |
| 276 | + description: "Deployment type is 'agent'" |
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