Turn AMC Workflows into Agent Skills

The operator question was practical: "We keep asking for the same AMC analyses. Can the agent remember the workflow instead of improvising every time?"

Yes, but the reusable unit should be a Skill, not a prompt snippet. A prompt remembers wording. A Skill remembers the steps: retrieve the right Amazon Marketing Cloud (AMC) playbook, choose the table, run the privacy or size check, produce the artifact, route the decision, and log what happened.

What a model without Atlas gets wrong

That is how a helpful demo becomes an unreviewable production process.

What Atlas retrieves

The agent starts by pulling the relevant Amazon Marketing Cloud playbooks from Amazon Agent Atlas. For an audience workflow, it retrieves:

• The audience-source rule that decides whether the Skill can use an audience-safe table.
• The sizing pattern that tells the operator whether the seed can activate.
• The activation timing and companion measurement guidance that belong beside the output.
• The AMC synthetic data playbook context when the Skill needs a safe test surface before it touches production workflows.

For a measurement workflow, it retrieves the attribution table, lookback rule, and caveats that belong in the output.

The Amazon Ads MCP gives the Skill live access to the Ads and AMC surfaces. Atlas tells it what the current playbook says before it acts.

The agent's working output

The useful output is a workflow contract:

{
  "skill": "amc_audience_workflow",
  "mode": "read_then_approve",
  "steps": [
    "retrieve_atlas_playbook",
    "resolve_table_window_filters",
    "run_privacy_and_seed_checks",
    "produce_sql_or_payload",
    "request_approval_for_writes",
    "write_run_log"
  ],
  "writeBoundary": "approval_required_before_dsp_activation"
}

That contract is deliberately more boring than an open-ended chat. Boring is what makes it repeatable.

The footnotes the agent surfaces

Those details are the difference between "the agent said so" and "we can audit the workflow."

What happens next

The full workflow runs through the Amazon Agent Data layer: Amazon Ads MCP brings AMC and demand-side platform (DSP) campaign signals, the Selling Partner MCP can add catalog context, Atlas grounds the operating procedure, and Skills turn the workflow into a reviewed recurring automation.

Once the Skill exists, the same workflow can run from chat, code, or an automation tool. The interface changes; the source rules and approval gates do not.

The point

A Skill is how an agent stops improvising an operating procedure.

Next: use durable run logs to make every Skill execution reviewable after the fact.

{"skill":"amc_audience_workflow","mode":"read_then_approve","requires":["atlas_retrieval","mcp_tool_parameters","approval_policy","run_log"]}