Build Signals Agent

---

name: build-signals-agent description: Use when building an AdCP signals agent, creating an audience data server, or standing up a data provider agent that serves targeting segments to buyers.

Build a Signals Agent

Overview

A signals agent serves audience segments to buyers for campaign targeting. Two tools: get_signals (discovery) and activate_signal (push to DSPs or sales agents). The business model — marketplace vs owned data — shapes every implementation decision. Determine that first.

When to Use

• User wants to build an agent that serves audience/targeting data
• User mentions signals, segments, audiences, data provider, or CDP in the context of AdCP
• User references get_signals, activate_signal, or the signals protocol

Not this skill:

• Selling ad inventory (products, packages, media buys) → skills/build-seller-agent/
• Rendering creatives from briefs → that's a creative agent
• Building a client that calls a signals agent → see docs/getting-started.md

Before Writing Code

Determine these four things. Ask the user — don't guess.

1. Marketplace or Owned?

These are fundamentally different businesses.

Marketplace — aggregates third-party data providers (LiveRamp, Oracle Data Cloud, Lotame). Each signal traces to a data_provider_domain that buyers can verify via adagents.json. signal_type: "marketplace", signal_id.source: "catalog".

Owned — first-party data (retailer CDP, publisher contextual, CRM). Buyers trust your agent directly. signal_type: "owned" or "custom", signal_id.source: "agent".

2. What Segments?

Get specifics: names, definitions, what each represents. Push for 3-5 segments with variety. Each needs:

• Clear behavioral/demographic definition
• Realistic coverage_percentage (typically 5-30%)
• Value type: binary (in/out), categorical (tier levels — define the categories), or numeric (score range — define min/max)

3. Pricing

At least one pricing option per signal. Signals use VendorPricingOption (field: model), distinct from product PricingOption (field: pricing_model).

• cpm — { pricing_option_id: "po_cpm", model: "cpm", cpm: 2.50, currency: "USD" }
• percent_of_media — { pricing_option_id: "po_pom", model: "percent_of_media", percent: 15, currency: "USD" }
• flat_fee — { pricing_option_id: "po_flat", model: "flat_fee", amount: 5000, period: "monthly", currency: "USD" }

4. Activation Destinations

If implementing activate_signal:

• Platform (DSP): type: "platform", returns activation_key: { type: "segment_id", segment_id: "..." }
• Agent (sales agent): type: "agent", returns activation_key: { type: "key_value", key: "...", value: "..." }

Tools and Required Response Shapes

get_adcp_capabilities — register first, empty {} schema

capabilitiesResponse({
  adcp: { major_versions: [3] },
  supported_protocols: ['signals'],
})

get_signals — GetSignalsRequestSchema.shape

Two discovery modes — support both:

1. signal_spec — natural language. Match against segment names and descriptions.
2. signal_ids — exact lookup by { source, data_provider_domain, id } or { source, agent_url, id }.

Plus filtering via filters.catalog_types, filters.max_cpm, filters.min_coverage_percentage, and max_results.

getSignalsResponse({
  signals: [{
    signal_agent_segment_id: string,  // required - key for activate_signal
    name: string,                     // required
    description: string,              // required
    signal_type: 'marketplace' | 'owned' | 'custom',  // required
    data_provider: string,            // required - your company name
    coverage_percentage: number,      // required - 0 to 100
    deployments: [],                  // required - empty array (not live until activated)
    pricing_options: [{               // required - at least one
      pricing_option_id: string,      // required
      model: 'cpm',                   // required - discriminator
      cpm: number,                    // required for cpm model
      currency: 'USD',               // required
    }],
    // signal_id is critical — shape depends on marketplace vs owned:
    signal_id: {
      source: 'catalog',             // marketplace
      data_provider_domain: string,  // marketplace — domain for provenance verification
      id: string,                    // unique segment ID
    },
    // OR for owned:
    signal_id: {
      source: 'agent',              // owned
      agent_url: string,            // your agent URL
      id: string,
    },
    value_type: 'binary' | 'categorical' | 'numeric',  // optional but recommended
  }],
  sandbox: true,  // for mock data
})

activate_signal — ActivateSignalRequestSchema.shape

Look up by signal_agent_segment_id. Validate pricing_option_id. Return deployments matching the requested destinations.

activateSignalResponse({
  deployments: [{
    // Match the destination type from the request:
    type: 'platform',              // for platform destinations
    platform: string,              // echo from request destination
    account: string | null,        // echo from request
    is_live: true,                 // signal is now active
    activation_key: {
      type: 'segment_id',
      segment_id: string,          // platform-specific segment ID
    },
  }],
  // OR for agent destinations:
  deployments: [{
    type: 'agent',
    agent_url: string,
    is_live: true,
    activation_key: {
      type: 'key_value',
      key: string,
      value: string,
    },
  }],
  sandbox: true,
})

SDK Quick Reference

SDK piece	Usage
serve(createAgent)	Start HTTP server on :3001/mcp
createTaskCapableServer(name, version, { taskStore })	Create MCP server with task support
server.tool(name, Schema.shape, handler)	Register tool — .shape unwraps Zod
capabilitiesResponse(data)	Build get_adcp_capabilities response
getSignalsResponse(data)	Build get_signals response
activateSignalResponse(data)	Build activate_signal response
taskToolResponse(data, summary)	Build generic tool response (for tools without a dedicated builder)
adcpError(code, { message })	Structured error (SIGNAL_NOT_FOUND, INVALID_DESTINATION)
GetSignalsRequestSchema.shape	Zod schema for get_signals input
ActivateSignalRequestSchema.shape	Zod schema for activate_signal input
type Signal = GetSignalsResponse['signals'][number]	Type for a single signal object

Import everything from @adcp/sdk. Types from @adcp/sdk with import type.

Setup

npm init -y
npm install @adcp/sdk
npm install -D typescript @types/node

Minimal tsconfig.json:

{
  "compilerOptions": {
    "target": "ES2022",
    "module": "Node16",
    "moduleResolution": "Node16",
    "strict": true,
    "skipLibCheck": true,
    "outDir": "dist"
  }
}

skipLibCheck: true avoids false-positive errors from transitive .d.ts files (e.g., @opentelemetry/api).

Implementation

1. Single .ts file — all tools in one file
2. Always register get_adcp_capabilities as the first tool with empty {} schema
3. Use Schema.shape (not Schema) when registering tools
4. Set sandbox: true for mock/demo data
5. Use ServeContext pattern: function createAgent({ taskStore }: ServeContext)

The skill contains everything you need. Do not read additional docs before writing code.

Validation

After writing the agent, validate it. Fix failures. Repeat.

Full validation (if you can bind ports):

npx tsx agent.ts &
npx @adcp/sdk@latest storyboard run http://localhost:3001/mcp signal_owned --json       # for owned data
npx @adcp/sdk@latest storyboard run http://localhost:3001/mcp signal_marketplace --json  # for marketplace

Sandbox validation (if ports are blocked):

npx tsc --noEmit agent.ts

Keep iterating until all steps pass.

Common Mistakes

Mistake	Fix
Pass Schema instead of Schema.shape	MCP SDK needs unwrapped Zod fields
Skip get_adcp_capabilities	Must be the first tool registered
Missing signal_agent_segment_id on signals	Buyers can't activate without it
Wrong signal_id shape	Marketplace: { source: "catalog", data_provider_domain, id }. Owned: { source: "agent", agent_url, id }
Missing data_provider field	Required on every signal — your company/brand name
Empty pricing_options array	Must have at least one pricing option per signal
is_live: true in get_signals deployments	Signals aren't live until activate_signal — use empty deployments: []
Activation doesn't match destination type	If request has type: "platform", deployment must be type: "platform"
sandbox: false on mock data	Buyers may treat mock data as real

Reference

• examples/signals-agent.ts — complete runnable example
• storyboards/signal_marketplace.yaml — buyer call sequences for marketplace agent
• storyboards/signal_owned.yaml — call sequences for owned data agent
• docs/guides/BUILD-AN-AGENT.md — SDK patterns
• docs/TYPE-SUMMARY.md — curated type signatures
• docs/llms.txt — full protocol reference