email-sequence

email-sequence is a skill for Claude Code from mysticaltech/marketingskills. It costs 84 tokens per session (2,031 once invoked), scanned A, a copy of emails, MIT.

A guide for creating a series of automated emails sent to people at planned times or after specific actions. It covers sequences for welcoming users, teaching them, recovering inactive users, supporting purchases, and encouraging sales.

In plain words
What is it for?
Use it to plan or improve welcome emails, lead-nurturing campaigns, onboarding messages, re-engagement flows, post-purchase emails, and other automated email programs.
Why use it?
It helps each email serve one clear purpose instead of asking readers to do too many things at once. It also structures messages around what the recipient already knows and the action you want next.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the marketing-skills plugin — 25 skills shipped together

Good fit Use it to plan or improve welcome emails, lead-nurturing campaigns, onboarding messages, re-engagement flows, post-purchase emails, and other automated email programs.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mysticaltech/marketingskills/email-sequence
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add mysticaltech/marketingskills --skill email-sequence
Clone the repo
git clone --depth 1 https://github.com/mysticaltech/marketingskills

Made for: Claude Code.

Or install marketing-skills, the plugin that ships this one along with the rest of its 25 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for email-sequence

README.md
[![agentmods](https://agentmods.dev/badge/skills/mysticaltech/marketingskills/email-sequence.svg)](https://agentmods.dev/skills/mysticaltech/marketingskills/email-sequence)
Your own site
<a href="https://agentmods.dev/skills/mysticaltech/marketingskills/email-sequence"><img src="https://agentmods.dev/badge/skills/mysticaltech/marketingskills/email-sequence.svg" alt="Measured on agentmods" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,031 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 94% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00084 $0.02031
Opus 5 $0.00042 $0.01015
Sonnet 5 $0.00017 $0.00406
Haiku 4.5 $0.00008 $0.00203

Measured 8d ago against content hash a57f0966ba41, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

email-sequence scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

94% identical to emails — 18 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/email-sequence/SKILL.md · 306 lines

How it starts

The opening of the file, as written. The whole thing — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Email Sequence Design

You are an expert in email marketing and automation. Your goal is to create email sequences that nurture relationships, drive action, and move people toward conversion.

Initial Assessment

Check for product marketing context first: If .claude/product-marketing-context.md exists, read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Before creating a sequence, understand:

  1. Sequence Type

    • Welcome/onboarding sequence
    • Lead nurture sequence
    • Re-engagement sequence
    • Post-purchase sequence
    • Event-based sequence
    • Educational sequence
    • Sales sequence
  2. Audience Context

    • Who are they?
    • What triggered them into this sequence?
    • What do they already know/believe?
    • What's their current relationship with you?
  3. Goals

    • Primary conversion goal
    • Relationship-building goals
    • Segmentation goals
    • What defines success?

Core Principles

1. One Email, One Job

  • Each email has one primary purpose
  • One main CTA per email
  • Don't try to do everything

2. Value Before Ask

  • Lead with usefulness
  • Build trust through content
  • Earn the right to sell

3. Relevance Over Volume

  • Fewer, better emails win
  • Segment for relevance
  • Quality > frequency

4. Clear Path Forward

  • Every email moves them somewhere
  • Links should do something useful
  • Make next steps obvious

Email Sequence Strategy

Sequence Length

  • Welcome: 3-7 emails
  • Lead nurture: 5-10 emails
  • Onboarding: 5-10 emails
  • Re-engagement: 3-5 emails

Depends on:

  • Sales cycle length
  • Product complexity
  • Relationship stage

Timing/Delays

  • Welcome email: Immediately
  • Early sequence: 1-2 days apart
  • Nurture: 2-4 days apart
  • Long-term: Weekly or bi-weekly

Consider:

  • B2B: Avoid weekends
  • B2C: Test weekends
  • Time zones: Send at local time

Subject Line Strategy

  • Clear > Clever
  • Specific > Vague
  • Benefit or curiosity-driven
  • 40-60 characters ideal
  • Test emoji (they're polarizing)

Read the full file on GitHub · 306 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 306 lines · 84 tokens per session scan A a57f0966ba41

Subscribe to this mod's changes

email-sequence is a skill published in the GitHub repository mysticaltech/marketingskills (347 stars, last pushed 6mo ago), licensed MIT. It adds 84 tokens to every session and 2,031 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to emails, differing in 18 lines, and is treated as a copy.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens