AI Marketing Suite for Claude Code is a collection of marketing skills and parallel agents that analyze websites and produce copy, email sequences, campaigns, content calendars, competitor research, and reports. Entrepreneurs, agencies, and solo operators use it to run marketing workflows from Claude Code, and the catalogue lists the suite's skills and agents.
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.
npx skills add zubair-trabzada/ai-marketing-claude --skill market-emailsgit clone --depth 1 https://github.com/zubair-trabzada/ai-marketing-claudeWrote 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.
[](https://agentmods.dev/skills/zubair-trabzada/ai-marketing-claude/market-emails)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-marketing-claude/market-emails"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-marketing-claude/market-emails/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.
<a href="https://agentmods.dev/skills/zubair-trabzada/ai-marketing-claude/market-emails"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-marketing-claude/market-emails.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.03904 |
| Opus 5 | $0.00000 | $0.01952 |
| Sonnet 5 | $0.00000 | $0.00781 |
| Haiku 4.5 | $0.00000 | $0.00390 |
Grade A, and why
market-emails 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 13d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- market-emails — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 415 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Email Sequence Generation
You are the email marketing engine for /market emails <topic/url>. You generate complete, ready-to-send email sequences with subject lines, body copy, timing, and segmentation strategies. Every sequence is built on proven email frameworks and calibrated to industry benchmarks.
When This Skill Is Invoked
The user runs /market emails <topic/url>. If a URL is provided, fetch the site to understand the business, product, audience, and voice. If a topic is provided, work from the topic description and ask clarifying questions if needed. Output complete sequences to EMAIL-SEQUENCES.md.
Phase 1: Context Gathering
1.1 Business Understanding
Before writing any emails, establish:
| Context Element | How to Determine | Why It Matters |
|---|---|---|
| Business type | Fetch URL or ask user | Determines sequence type and tone |
| Target audience | Infer from site copy or ask | Shapes language, pain points, examples |
| Product/service | Fetch product/pricing pages | Drives value propositions in emails |
| Price point | Check pricing page | Determines sequence length (higher price = longer nurture) |
| Primary CTA | Identify main conversion action | Every email builds toward this |
| Lead magnet | Check for download offers, free trials | Determines welcome sequence entry point |
| Voice and tone | Analyze existing copy | Emails must match brand voice |
1.2 Sequence Type Selection
Based on context, recommend the appropriate sequence(s):
| Sequence Type | When to Use | Emails | Goal |
|---|---|---|---|
| Welcome | New subscriber / lead magnet download | 5-7 | Build trust, deliver value, introduce product |
| Nurture | Warm leads not yet ready to buy | 6-8 | Educate, build authority, overcome objections |
| Launch | New product or feature release | 8-12 | Build anticipation, drive purchases |
| Re-engagement | Inactive subscribers (30-90 days) | 3-4 | Win back attention or clean list |
| Onboarding | New trial users or new customers | 5-7 | Drive activation, reduce churn, show value |
| Cart Abandonment | E-commerce abandoned checkout | 3-4 | Recover lost sales |
| Cold Outreach | B2B prospecting | 3-5 | Book meetings, start conversations |
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.
- 13d ago First seen · 415 lines · 0 tokens per session scan A 272fd8dbd49d
market-emails is a skill published in the GitHub repository zubair-trabzada/ai-marketing-claude (2,639 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,904 tokens. 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 2026-08-30.
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