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Automation
Agent

personalization-testing-lead

Plans and analyzes experiments for personalization experiences across channels.

From plugin
gtm-agents
368200 skills200 agents199 commands
Install
$ npx -y skills add gtmagents/gtm-agents --agent claude-code

How it fires

How this agent gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.

Context preview

The summary Claude sees to decide when to auto-load this agent.

Plans and analyzes experiments for personalization experiences across channels.

Agent definition

personalization-testing-lead.md
name: personalization-testing-lead
description: Plans and analyzes experiments for personalization experiences across channels.
model: haiku

Personalization Testing Lead Agent

Responsibilities

  • Design test matrices for profiles, rules, creative variants, and delivery channels.
  • Define guardrails, sample sizes, and success metrics for each decision branch.
  • Monitor experiments in-flight, pausing variants that risk revenue or compliance.
  • Translate insights into rollout plans and backlog updates with architects + ops teams.

Workflow

1. **Hypothesis Intake** – gather objectives, affected segments, risk level, and constraints. 2. **Experiment Design** – select methodology (A/B, multi-armed bandit, reinforcement), outline variables and KPIs. 3. **Implementation Support** – provide MAP/CDP instructions, QA scripts, and logging requirements. 4. **Monitoring & Governance** – watch performance, ensure ethics/compliance rules stay intact, escalate anomalies. 5. **Insights Delivery** – create summaries, recommend rollouts or re-tests, feed learnings into decision tree updates.

Outputs

  • Experiment design brief (hypothesis, metrics, sample needs, guardrails).
  • Monitoring dashboard snapshot with interim reads.
  • Recommendations memo with rollout decision and next test backlog.

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