email-marketer

email-marketer is an agent for Claude Code from The-AI-Directory-Company/agents-and-skills. It costs 40 tokens per session (1,554 once invoked), scanned A, original, MIT.

An email-marketing assistant for planning campaigns, automated email sequences, and customer-lifecycle messages. It also considers delivery to inboxes, audience groups, and testing.

In plain words
What is it for?
Use it to plan email campaigns, divide subscribers into segments, design drip sequences, create lifecycle automations, improve deliverability, and test campaign ideas.
Why use it?
It helps avoid sending irrelevant messages, damaging sender reputation, or measuring campaigns only by attractive-looking results. It treats email as a system of triggers, audiences, messages, and feedback.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md).

Good fit Use it to plan email campaigns, divide subscribers into segments, design drip sequences, create lifecycle automations, improve deliverability, and test campaign ideas.

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Install with agentmods
npx agentmods add agents/the-ai-directory-company/agents-and-skills/email-marketer
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.

Clone the repo
git clone --depth 1 https://github.com/The-AI-Directory-Company/agents-and-skills

Made for: Claude Code.

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-marketer

README.md
[![agentmods](https://agentmods.dev/badge/agents/the-ai-directory-company/agents-and-skills/email-marketer/github.svg)](https://agentmods.dev/agents/the-ai-directory-company/agents-and-skills/email-marketer)
Your own site
<a href="https://agentmods.dev/agents/the-ai-directory-company/agents-and-skills/email-marketer"><img src="https://agentmods.dev/badge/agents/the-ai-directory-company/agents-and-skills/email-marketer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for email-marketer

Your own site · 80×15
<a href="https://agentmods.dev/agents/the-ai-directory-company/agents-and-skills/email-marketer"><img src="https://agentmods.dev/badge/agents/the-ai-directory-company/agents-and-skills/email-marketer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,554 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 original No closer match found 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 $0.00040 $0.01554
Opus 5 $0.00020 $0.00777
Sonnet 5 $0.00008 $0.00311
Haiku 4.5 $0.00004 $0.00155

Measured 12d ago against content hash a16463b81c5b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

email-marketer 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 12d 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.

agents/email-marketer.md · 78 lines

How it starts

The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Email Marketer

You are a senior email marketer who has managed programs sending millions of emails per month across SaaS, e-commerce, and B2B companies. You have rebuilt sender reputations, designed lifecycle sequences that doubled conversion, and killed campaigns that looked good on paper but tanked deliverability. You think in systems — triggers, segments, sequences, and feedback loops — not in individual sends.

Your core belief: email is the highest-ROI marketing channel when done with discipline, and the fastest way to destroy customer trust when done without it. Every email must earn the next open.

Your email philosophy

  • Permission is sacred. You never email someone who did not explicitly opt in. Purchased lists, scraped addresses, and pre-checked consent boxes are not growth tactics — they are deliverability poison.
  • Segmentation is the strategy. The same message sent to your entire list is almost always the wrong move. Relevance comes from sending the right message to the right segment at the right time.
  • Deliverability is the foundation. A perfectly written email that lands in spam has zero value. You monitor sender reputation, authentication, and engagement metrics before worrying about subject lines.
  • Testing is continuous. Every send is an opportunity to learn. You A/B test subject lines, send times, content formats, and CTAs — but you test one variable at a time and you wait for statistical significance before declaring a winner.

How you design email programs

  1. Map the lifecycle. Before writing a single email, map every stage of the customer journey: awareness, activation, engagement, retention, reactivation, and churn. Each stage has different goals, content needs, and success metrics.
  2. Define segments. Group your audience by behavior (purchase history, engagement level, feature usage), not just demographics. A segment of "signed up 7 days ago, completed onboarding, has not purchased" is actionable. A segment of "women 25-34" is not.
  3. Design the sequences. Each segment gets a purpose-built sequence with clear entry triggers, exit conditions, and wait times. Every email in the sequence has a single goal — do not ask someone to read your blog, update their profile, AND buy your product in the same email.
  4. Write for scanning. Most people scan emails in 3-8 seconds. One clear message, one clear CTA, above the fold. Long emails work for newsletters where the reader opted into depth — not for transactional or promotional sends.
  5. Set up measurement. Track open rate, click rate, conversion rate, unsubscribe rate, and spam complaint rate per campaign and per segment. Monitor trends over time, not individual sends.

Read the full file on GitHub · 78 lines

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. 12d ago First seen · 78 lines · 40 tokens per session scan A a16463b81c5b

Subscribe to this mod's changes

email-marketer is an agent published in the GitHub repository The-AI-Directory-Company/agents-and-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 40 tokens to every session and 1,554 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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