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-landinggit 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-landing)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-marketing-claude/market-landing"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-marketing-claude/market-landing/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-landing"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-marketing-claude/market-landing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 58 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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 | $0.03134 |
| Opus 5 | $0.00000 | $0.01567 |
| Sonnet 5 | $0.00000 | $0.00627 |
| Haiku 4.5 | $0.00000 | $0.00313 |
Grade A, and why
market-landing 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
2 near-identical copies found in the catalogue:
- market-landing — 100% identical, 0 lines differ
- market-landing — 97% identical, 5 lines differ
How it starts
The opening of the file, as written. The whole thing — 329 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Landing Page CRO Analysis
Skill Purpose
Perform a comprehensive Conversion Rate Optimization (CRO) analysis on any landing page. This skill produces a section-by-section teardown with prioritized, actionable fixes that directly impact conversion rates.
When to Use
- User provides a landing page URL and asks for conversion optimization
- User asks for landing page feedback, review, or audit
- User wants to improve signup, lead capture, or purchase rates
- Triggered by
/market landing <url>or/market cro <url>
How to Execute
Step 1: Identify the Page Type
Determine which type of landing page you are analyzing. This affects benchmark expectations and scoring weights.
| Page Type | Primary Goal | Good CR | Great CR |
|---|---|---|---|
| Lead Capture | Email/form submission | 5-10% | 15%+ |
| SaaS Signup | Free trial or freemium signup | 3-7% | 10%+ |
| E-commerce Product | Add to cart / Purchase | 2-4% | 5%+ |
| Webinar Registration | Register for event | 20-30% | 40%+ |
| App Download | Install app | 10-15% | 20%+ |
| Waitlist | Join waitlist | 15-25% | 35%+ |
| Consultation Booking | Schedule a call | 5-10% | 15%+ |
| Nonprofit Donation | Make a donation | 2-5% | 8%+ |
Step 2: Run the 7-Point CRO Framework
Analyze each section in order. Score each section 1-10 and provide specific findings.
Section 1: Hero Section (Weight: 25%)
The first screen a visitor sees. This is where 80% of conversion decisions begin.
Checklist:
- Headline is visible within 2 seconds of page load
- Headline communicates the primary benefit (not a feature)
- Headline is under 10 words
- Subheadline expands on the headline with specificity
- Primary CTA is above the fold
- CTA button color contrasts with the background
- CTA text is action-oriented (not "Submit" or "Click Here")
- Hero image or video supports the message (not generic stock)
- Trust badges or social proof visible above the fold
- Page loads in under 3 seconds
- No navigation menu competing with the CTA (for dedicated landing pages)
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 · 329 lines · 0 tokens per session scan A c3c187ddd9d9
market-landing 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 3,134 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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