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Claudeemailmarketing

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Use when Codex, Hermes, OpenClaw, Claude Code, Cowork, or another AI agent needs to plan, review, implement, audit, or improve email work focused on Claude-assisted positioning, segmentation, lifecycle content, and marketing review systems. Triggers include requests about offer refinement, segment-specific messaging, lifecycle copy reviews, positioning tests, and campaign strategy.

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  • Added September 3, 2026
ai-agentstesting

Works with

  • claude code

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Scanned September 3, 2026

npx -y skills add aiskillstore/marketplace --skill claudeemailmarketing --agent claude-code

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SKILL.md
---
name: claudeemailmarketing
description: "Use when Codex, Hermes, OpenClaw, Claude Code, Cowork, or another AI agent needs to plan, review, implement, audit, or improve email work focused on Claude-assisted positioning, segmentation, lifecycle content, and marketing review systems. Triggers include requests about offer refinement, segment-specific messaging, lifecycle copy reviews, positioning tests, and campaign strategy."
---

# Claude Email Marketing Skill

Use Claude as a strategist and critic, not an autopilot. Anchor every message in a segment, a belief change, and a measurable next step.

## Agent Contract

The agent may inspect, reason, draft, critique, and prepare handoffs for Claude-assisted positioning, segmentation, lifecycle content, and marketing review systems.

- Primary lens: Claude-assisted positioning, segmentation, lifecycle content, and marketing review systems.
- Common request signals: offer refinement, segment-specific messaging, lifecycle copy reviews, positioning tests, and campaign strategy.
- Default posture: Use Claude as a strategist and critic, not an autopilot. Anchor every message in a segment, a belief change, and a measurable next step.
- Useful output family: positioning briefs, segment message matrices, Claude prompt packs, lifecycle copy reviews, experiment plans, and campaign recommendations.
- Production boundary: separate recommendation from execution.
- Evidence boundary: say which source material supports the recommendation.
- Review boundary: identify the human owner for risky changes.

## Use Cases

Typical requests include offer refinement, segment-specific messaging, lifecycle copy reviews, positioning tests, and campaign strategy.

## Runbook

- Clarify the commercial job: activate, educate, convert, expand, retain, recover, announce, or research.
- Define the segment by situation and intent, not just demographics or list membership.
- Turn positioning into an email angle: problem frame, contrast, proof, mechanism, objection, and CTA.
- Ask Claude to generate or critique only within approved evidence and brand constraints.
- Compare variants by strategy: audience fit, differentiation, proof density, urgency, risk, and measurement plan.
- Return the marketing decision, not only the copy: what to send, to whom, why now, and how success will be judged.

## Quality Bar

- The segment has a reason to care today.
- The message says something more specific than a generic benefit.
- Proof supports the offer without inventing social proof or guarantees.
- The CTA matches funnel stage and commitment level.
- Testing recommendations isolate one meaningful variable.

## Output Pattern

Return positioning briefs, segment message matrices, Claude prompt packs, lifecycle copy reviews, experiment plans, and campaign recommendations. Keep recommendations concrete. Separate analysis from live-system actions, and require explicit approval before sending email, importing contacts, changing DNS, altering suppression rules, or editing production automations.

Files in this skill

  • SKILL.md3 KB
  • agents/openai.yaml289 B
  • references/operating-checklist.md1.4 KB
  • skill-report.json9 KB

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