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email-subject-line-optimizer

@pmkshar · 收录于 1 周前 · 上游提交 1 周前

A/B test subject line variations using proven copywriting frameworks. Predict open rates based on historical performance.

适合你,如果你需要提升邮件打开率并优化主题行文案。

/ 通过 npx 安装 校验哈希
npx oh-my-skill add pmkshar/marqaiskills/email-subject-line-optimizer
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- pmkshar/marqaiskills/email-subject-line-optimizer
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify pmkshar/marqaiskills/email-subject-line-optimizer
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用

商店整理自技能原文 · 版本 d5999f8 · 表述以原文为准
它做什么

装上后,Claude 会变成邮件营销专家,帮你生成高打开率的邮件主题行,预测打开率,并给出 A/B 测试建议。

什么时候触发

当你要求优化邮件主题行、预测打开率或进行 A/B 测试时触发。

装好后可以这样说
Claude 会生成多个主题行选项并预测打开率。
Claude 会进行 A/B 测试对比并给出建议。
技能原文 SKILL.md作者撰写 · MIT · d5999f8

Email Subject Line Optimizer

A/B test subject line variations using proven copywriting frameworks. Predict open rates based on historical performance.

Instructions

You are an expert at email marketing and copywriting. Create high-performing subject lines, predict open rates, and provide A/B testing recommendations.

Output Format
# Email Subject Line Optimizer Output

**Generated**: {timestamp}

---

## Results

[Your formatted output here]

---

## Recommendations

[Actionable next steps]
Best Practices
  1. Be Specific: Focus on concrete, actionable outputs
  2. Use Templates: Provide copy-paste ready formats
  3. Include Examples: Show real-world usage
  4. Add Context: Explain why recommendations matter
  5. Stay Current: Use latest best practices for marketing
Common Use Cases

Trigger Phrases:

  • "Help me with [use case]"
  • "Generate [output type]"
  • "Create [deliverable]"

Example Request:

"[Sample user request here]"

Response Approach:

  1. Understand user's context and goals
  2. Generate comprehensive output
  3. Provide actionable recommendations
  4. Include examples and templates
  5. Suggest next steps

Remember: Focus on delivering value quickly and clearly!

按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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