The AI email automation skill for Claude, ChatGPT, and any agent.
Install it and your AI stops guessing about email. It audits your setup, builds your flows from a prompt, drafts copy in your voice (not slop), tells you why you are in spam, and runs your ESP through MCP, with a hard rule that nothing blasts without your say-so.
Built from 908 sources and the experience of running SmartrMail (email marketing SaaS, ~28,000 customers, 6 billion emails, acquired 2022). 17 chapters, 19 industry playbooks, 47 curated email designs. Free and open source.
Most email marketing advice is surface-level. "Personalise your subject lines." "Segment your list." "A/B test everything." You have heard it. It does not help when you are staring at a 2% open rate, or when you have just handed an AI agent the keys to your sending account and it is about to industrialise your mistakes.
In 2026 the job changed. Agents now build the campaign, segment the audience, draft the copy, and stage the send. The marketer is the director, not the operator. That only works if the agent is working from real benchmarks and hard guardrails instead of vibes. This skill is that discipline layer: the patterns that repeat across industries, the mistakes that destroy deliverability, the anti-slop rules that keep AI output from reading like AI output, and the send-safety gates that keep one prompt from mailing the wrong thing to your whole list.
Every claim is backed by data. No theory, no filler.
git clone https://github.com/CosmoBlk/email-marketing-bible.git ~/.claude/skills/email-marketing-bibleOne command. Your AI now has the full knowledge base. Works wherever you run skills (Claude Code, Claude Desktop, and agents that read the skill format).
Once installed, your AI can:
| Task | What it does |
|---|---|
| Run email automation | Build welcome, cart, post-purchase, and win-back flows from a prompt, then review exits, timing, and copy before anything goes live |
| Audit your setup | Review flows, segments, deliverability, and compliance, and tell you exactly what is missing |
| Draft and de-slop copy | Write emails with proven frameworks (PAS, AIDA, BAB) and strip the AI tells before send |
| Design anti-slop emails | Own a colour, real imagery, live-text headlines, generated into inbox-safe MJML or React Email, dark-mode and mobile checked |
| Drive your ESP from AI | Operate Klaviyo, Resend, beehiiv, Mailchimp, Omnisend, or nitrosend through MCP and connectors, with pre-send safety gates |
| Fix deliverability | Diagnose inbox placement with a step-by-step triage covering authentication, reputation, content, and the AI-mediated inbox (Gemini summaries, open rate as noise) |
| Pull industry benchmarks | Open, click, conversion, and revenue-per-email figures for your specific vertical |
| Compare platforms | Honest comparison by list size, budget, and whether you want to run it from an agent, not affiliate commissions |
| Review compliance | GDPR, CAN-SPAM, CASL, CCPA, and the Australian Spam Act, as a decision gate before any send |
| Write cold email | Cold sequences with proper infrastructure separation, warming, and personalisation |
Install the skill, then talk to your AI like an email marketing consultant.
Audit and build:
"Audit my Klaviyo account for a DTC skincare brand doing $2M/year. I have a
welcome series, abandoned cart, and one weekly newsletter. What am I missing,
and build me whatever flow would earn the most first."
Fix a problem:
"My emails are landing in Gmail promotions and opens dropped from 22% to 14%
over three months. What is going on and how do I fix it?"
De-slop:
"Here is a draft welcome email. Make it sound like a person, not an AI, and
keep it on our brand voice."
Design:
"Design a launch email for a premium coffee brand. Own a colour, real product
photography, generate it as MJML so it renders everywhere."
The skill is structured in two parts: an operating manual (when the AI is acting: building, sending, diagnosing, designing) and a dense reference (benchmarks, frameworks, playbooks). Your AI reads the manual to operate and drops into the reference for facts.
| # | Chapter | What you get |
|---|---|---|
| 1 | The Fundamentals | Why email wins, the stack, key metrics, the AI-mediated inbox |
| 2 | Building Your List | Organic growth, popups, opt-in, spam traps, validation |
| 3 | Segmentation & Personalisation | Engagement tiers, AI-built segments, 1:1 content from behaviour |
| 4 | The Emails That Make Money | Welcome, cart, post-purchase, win-back, and building flows with AI |
| 5 | Copywriting That Converts | Subject lines, frameworks, CTAs, and the anti-slop copy protocol |
| 6 | Design & Technical | Mobile, dark mode, accessibility, anti-slop and prompted design |
| 7 | Deliverability | SPF, DKIM, DMARC, BIMI, reputation, warming, autonomous-send safety |
| 8 | Testing & Optimisation | A/B testing, significance, send-time, testing AI-assisted email |
| 9 | Analytics & Measurement | KPIs by type, attribution, querying your data with AI |
| 10 | Compliance & Privacy | GDPR, CAN-SPAM, CASL, CCPA, AU Spam Act, AI accountability |
| 11 | Industry Playbooks | Tactics for 19 verticals (see below) |
| 12 | Choosing Your Platform | Honest comparison, including which tools an agent can actually drive |
| 13 | Cold Email & B2B Outbound | Infrastructure, writing, follow-up, AI in outbound |
| 14 | AI Email Automation | The operating model, agent guardrails, MCP and connectors, what to automate |
| 15 | Company Case Studies | How Casper, Morning Brew, Duolingo, Spotify, and others use email |
| 16 | Expert Directory | The practitioners referenced throughout, who to follow and why |
| 17 | Best Email Designs 2026 | 47 hand-curated emails with notes on why each works and what to steal |
Plus four appendices: benchmarks by industry, frequency guide, marketing calendar, and methodology.
Ecommerce DTC · SaaS B2B · SaaS B2C · Newsletter & Creator · Agency · Nonprofit · Healthcare · Financial Services · Real Estate · Travel & Hospitality · Education · Professional Services · Retail · Events · B2B Manufacturing · Restaurant & Food · Fitness · Media & Publishing · Marketplace & Platform
Insights from practitioners including Chad S. White (Zeta Global), Joanna Wiebe (Copyhackers), Chase Dimond (Structured Agency), Nathan Barry (Kit), Ann Handley (MarketingProfs), Troy Ericson, Tyler Denk (beehiiv), Ben Settle, and many others. Full directory in Chapter 16.
The complete Email Marketing Bible is at emailmarketingskill.com, searchable and browsable, with all 17 chapters and 4 appendices, plus a free PDF.
908 sources across industry reports (Litmus, Klaviyo, HubSpot, Salesforce, Validity), practitioner blogs, podcasts and transcripts, platform documentation, and community discussions, refreshed mid-2026 with a focus on AI email automation.
Found an error? Have better data? Know a tactic that is missing? Issues and PRs welcome. The more practitioners contribute, the better it gets.
MIT. Use it however you want.
Built by George Hartley. Follow for updates.