Show HN: I built a 55K-word email marketing knowledge base and Claude Code skill

Source: Hacker News

My Research Process

Multiple sprints across all major email‑marketing topics. The crawler pulled 908 sources: Litmus, Klaviyo, HubSpot, Campaign Monitor, and Salesforce annual reports; practitioner blogs; academic research; platform documentation; Reddit threads; Shopify forums; and community discussions on X. From those, I extracted 4,798 discrete insights. Every claim that made it into the guide has a source; anything that was unsourced opinion was cut.

That produced EMB v4: over 80 k words across 16 chapters. After two editorial passes—cutting duplicates, consolidating overlapping sections, and removing anything that didn’t earn its place—it landed at 55 000 words. I reached out to all the email experts cited for feedback; over half contributed and made changes.

The Skill vs. Bible Issue

The full 55 k‑word guide is too big for a context window. You can’t just point Claude at the whole thing and expect coherent answers.

So the SKILL.md is a separate, condensed extraction: the key frameworks, benchmarks, practitioner names, and tactical thresholds that fit in context. When you ask Claude a question with the skill installed, it draws on a structured summary rather than trying to retrieve from a raw document dump.

The problem is that the skill and the “Bible” can drift. As the Bible gets updated (experts send corrections, better data emerges), the skill needs to be manually kept in sync. The obvious fix is an MCP server that connects them so changes to the Bible automatically propagate to the skill. I’ll probably build that with the next big update to the Bible.

The Data Gap

I saw on SmartrMail that occasionally “conversion wisdom” or email best practices would not line up with our real, aggregate sending data. Example: “best time of the week to send a newsletter is 9 am Tue/Thu.” In practice, it was a case‑by‑case solution, and the rule of thumb would often hurt engagement.

The weakness of this project is that it’s built on published research, not proprietary sending data. Published benchmarks are backward‑looking, aggregated across wildly different use cases, and often produced by ESPs with an incentive to make email look good.

What I’d really want is anonymised send‑level data from real campaigns, e.g.:

• Subject line → open rate, across list sizes, industries, send times
• Body structure → click rate
• Flow configuration → revenue per recipient

If anyone is working on this or has access to send‑level data and wants to contribute, I’m very interested.

The ESP Integration Problem

AI connections into ESPs are still terrible. Most platforms have API coverage for basic CRUD operations but nothing close to what you’d need to actually run a campaign from Claude. You can pull subscriber counts, but you can’t meaningfully analyse flow performance, trigger segment rebuilds, or get real deliverability diagnostics programmatically.

A few ESPs are starting to add MCP servers (mentioned in Chapter 14 of the guide), but it’s early and patchy. Until that’s solved, the skill is advisory—it can tell you what to do, but it can’t do it for you. That gap is worth building toward.

What’s Live Now

Install

git clone https://github.com/CosmoBlk/email-marketing-bible.git ~/.claude/skills/email-marketing-bible

• Website:
• MIT licensed. No paywall. No email gate. No affiliate links.

Happy to answer questions!

Comments URL: (Points: 6) (Comments: 1)