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Agent Skill · 待分类

send-email-campaign(发送电子邮件活动)

send-email-campaign 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

send-email-campaign 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描有提醒项,按安装量在待分类类的 11,209 个 Skill 里排第 5,090。

总安装 618周安装 26GitHub Stars 66下载 216核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:send-email-campaign(发送电子邮件活动)
来源仓库:https://github.com/indranilbanerjee/digital-marketing-pro
仓库路径:skills/send-email-campaign
安装命令:
npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill send-email-campaign
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill send-email-campaign

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库和原始 README 核验具体用法。安装方式:通过 npx skills add 命令从指定 GitHub 仓库添加。

注意权限范围和维护状态,确认是否会触发联网、命令执行或文件读写。

来源仓库内路径:skills/send-email-campaign

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

send-email-campaign 怎么安装?

在终端执行 npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill send-emai…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

send-email-campaign 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

send-email-campaign 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

send-email-campaign 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

send-email-campaign 用的人多吗?

公开数据是累计安装 618 次,近一周安装 26 次,下载 216 次,GitHub 66 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

send-email-campaign 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
send-email-campaign

发送电子邮件活动 · 本页

61866调用外部服务未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

/dm:send-email-campaign

Purpose

Create and send a targeted email campaign through the brand's connected email platform with personalization, A/B subject lines, compliance checks, and deliverability monitoring. Handles the full lifecycle from content validation through send execution to post-send monitoring, with tiered risk controls based on recipient list size. Ensures every send passes spam, compliance, and brand voice gates before reaching any inbox.

Input Required

The user must provide (or will be prompted for):

  • Email content: Subject line, preview text (40-90 chars), body copy with HTML structure, and primary CTA — or a draft to refine
  • Target list or segment: The recipient list name, segment ID, or audience criteria for the send — with confirmation of list hygiene status (last cleaned date)
  • Email platform: Which email service to use — SendGrid, Klaviyo, Customer.io, Brevo, or Mailgun — must have the corresponding MCP server connected
  • Personalization fields: Dynamic fields to personalize — first name, company, product interest, last purchase, location, or custom merge tags with fallback defaults for missing data
  • A/B variants: Optional — 2-3 subject line or content variants for split testing with desired test percentage (10-50%), test duration, and winning metric (open rate or click rate)
  • Send time: Immediate send, scheduled date and time with timezone, or "optimal" to use send-time optimization based on historical engagement data per segment
  • Reply-to address: Reply-to email address if different from the default sender configured in the platform
  • Sender name and from address: Display name and from address — must match authenticated sending domain (SPF, DKIM, DMARC)
  • Unsubscribe handling: Confirm unsubscribe link placement, one-click unsubscribe header compliance (required for bulk senders per Gmail/Yahoo 2024 rules), and preference center link
  • UTM tracking: Google Analytics UTM parameters for all links in the email body (source, medium, campaign), or auto-generate based on brand naming conventions
  • Suppression list: Any additional email addresses or domains to exclude from this send beyond the platform's global suppression list
  • Email template: Optional — platform template ID to use, or build from scratch with the provided content and brand styling
  • Preheader text strategy: Whether the preview text should complement, tease, or extend the subject line — affects how the email appears in inbox list view
  • Fallback content: Plain-text version of the email for recipients whose clients do not render HTML, or auto-generate from the HTML body

Process

  1. Load brand context: Read ~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json. Apply brand voice, compliance rules for target markets (skills/context-engine/compliance-rules.md), and industry context. Also check for guidelines at ~/.claude-marketing/brands/{slug}/guidelines/_manifest.json — if present, load restrictions. Check for agency SOPs at ~/.claude-marketing/sops/. If no brand exists, ask: "Set up a brand first (/dm:brand-setup)?" — or proceed with defaults.
  2. Verify email platform connection: Check which email MCP server is connected and confirm it matches the user's target platform. Verify the sending domain is authenticated (SPF, DKIM, DMARC records). If not connected or not authenticated, instruct the user on setup steps.
  3. Score email subject lines: Run email-subject-tester.py on all subject line variants to evaluate length (optimal 30-50 chars), power words, personalization token effectiveness, emoji usage, and predicted open rate. Recommend improvements if any variant scores below threshold.
  4. Check spam score: Run spam-score-checker.py to analyze subject lines and body content for spam trigger words, excessive capitalization, exclamation marks, link-to-text ratio, image-to-text ratio, and authentication alignment. Flag any deliverability risks with specific remediation steps.
  5. Optimize send time: If the user selected "optimal" timing, run send-time-optimizer.py with historical engagement data to determine the best send window by day of week and hour for the target segment. Factor in timezone distribution of the recipient list.
  6. Build platform-specific payload: Structure the email payload per the target platform's API requirements — consult platform-publishing-specs.md for field mappings, template rendering, merge tag syntax (e.g., {{first_name}} vs {first_name}), A/B test configuration parameters, and scheduling API format.
  7. Verify list size and consent compliance: Confirm recipient count and segment definition. Check that the list has proper opt-in consent flags for the applicable jurisdiction. Verify unsubscribe mechanism is functional, one-click unsubscribe header is present, physical mailing address is included, and compliance with CAN-SPAM (US), GDPR (EU), CASL (Canada), and any other regulations for the brand's target markets.
  8. Score brand voice: Run brand-voice-scorer.py on the email body content to verify alignment with brand tone and messaging guidelines. Flag any copy that deviates from brand standards.
  9. Create approval record: Run approval-manager.py with tiered risk levels — medium for fewer than 1,000 recipients, high for 1,000-10,000, critical for more than 10,000. Generate a send summary with all campaign details, scores, and compliance status.
  10. Present campaign summary: Display the complete summary for user review — subject lines with scores, preview text, recipient count and segment name, send time, personalization preview with sample recipient data, spam score, brand voice score, and compliance checklist. Wait for explicit confirmation.
  11. Send test email: On initial approval, send a test email to the user's address (and any additional test addresses) via the MCP server. Ask the user to confirm the test renders correctly across desktop and mobile, personalization tokens resolve, links work, and images load.
  12. Execute full send via MCP: After test confirmation, trigger the campaign send through the connected email platform MCP. Handle A/B test split configuration, scheduling, and any platform-specific send options (track opens, track clicks, Google Analytics UTM tagging).
  13. Monitor deliverability: After send, poll the platform API at 15-minute intervals for the first hour to track delivery metrics — bounce rate, delivery rate, soft bounces, hard bounces, and spam complaints. Alert the user if bounce rate exceeds 3% or spam complaint rate exceeds 0.1%.
  14. Capture early engagement signals: After 1 hour and again at 4 hours, pull open rate and click rate data. Compare against the brand's historical averages for the same segment. If A/B testing, report which variant is leading.
  15. Log execution: Run execution-tracker.py to log the send event with timestamp, platform, campaign ID, list size, subject lines, A/B configuration, send time, initial delivery metrics, and compliance verification status. Save an insight about subject line performance for future email strategy optimization.

Output

A structured send confirmation containing:

  • Send confirmation: Campaign ID, platform, send status (sent, scheduled, or A/B testing), and timestamp with timezone
  • List details: Recipient count, segment name, consent verification status, and list hygiene notes
  • Subject line scores: Score breakdown for each variant — length, power words, personalization effectiveness, predicted open rate, and spam risk indicators
  • Spam score report: Overall deliverability risk rating (low/medium/high) with specific flags for any triggered spam indicators and remediation steps
  • Brand voice score: Email content alignment score with notes on tone consistency and any copy adjustments recommended
  • Send time: Actual send time with rationale — user-specified, scheduled with timezone, or optimized with supporting engagement data
  • A/B test configuration: If applicable — variant descriptions, split percentage, test duration, winning metric, and auto-send winner settings
  • Deliverability report: Initial delivery rate, bounce rate (hard and soft), spam complaint rate, and comparison against industry benchmarks for the brand's sector
  • Compliance checklist: Pass/fail for CAN-SPAM, GDPR, CASL, unsubscribe mechanism, one-click unsubscribe header, physical address, authentication headers (SPF, DKIM, DMARC), and sender identity
  • Early engagement signals: 1-hour and 4-hour open rate and click rate snapshots with comparison to brand historical averages and industry benchmarks
  • Personalization preview: Sample rendering showing how the email appears for 2-3 representative recipients with different merge tag values and fallback defaults
  • UTM tracking summary: Complete UTM parameters applied to all email links for attribution tracking in the brand's analytics platform
  • Execution log entry: Timestamped record of the send action with all campaign metadata for audit trail and performance benchmarking

Agents Used

  • email-specialist — Subject line optimization, content personalization strategy, deliverability analysis, spam scoring, send time optimization, compliance verification, brand voice scoring, A/B test design with statistical significance thresholds, and preheader text strategy
  • execution-coordinator — Approval workflow with tiered risk controls based on list size, test send coordination across desktop and mobile, platform API execution, deliverability monitoring with real-time alerting, early engagement signal capture, and execution logging with insight archival

平台分布

Codex

35.59%
按下载量换算77

Claude

30.81%
按下载量换算67

Cursor

16.32%
按下载量换算35

Gemini CLI

9.42%
按下载量换算20

安全审计

Gen Agent Trust Hub

可疑

Socket

可疑

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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