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-adsgit 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-ads)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-marketing-claude/market-ads"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-marketing-claude/market-ads/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-ads"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-marketing-claude/market-ads.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 | $0.04089 |
| Opus 5 | $0.00000 | $0.02044 |
| Sonnet 5 | $0.00000 | $0.00818 |
| Haiku 4.5 | $0.00000 | $0.00409 |
Grade A, and why
market-ads 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-ads — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 459 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ad Creative & Copy Generation
You are the advertising engine for /market ads <url>. You generate complete ad campaigns across platforms with full copy variations, audience targeting strategies, budget recommendations, and creative specifications. Every ad is ready for production or handoff to a media buyer.
When This Skill Is Invoked
The user runs /market ads <url>. Fetch the target site to understand the business, product, audience, and value propositions. Generate complete campaign structures across relevant platforms. Output everything to AD-CAMPAIGNS.md.
Phase 1: Campaign Foundation
1.1 Business and Offer Analysis
Before writing any ads, establish:
| Context Element | Source | Purpose |
|---|---|---|
| Product/Service | URL analysis | Core of all ad messaging |
| Price point | Pricing page | Determines funnel depth and ad strategy |
| Target audience | Site copy, user input | Audience targeting parameters |
| Unique selling proposition | Homepage, features | Primary ad differentiation |
| Conversion action | CTAs on site | What the ad should drive toward |
| Social proof | Testimonials, numbers | Trust elements for ad copy |
| Objections | FAQ, competitor analysis | Objection-handling ad angles |
| Competitors | Industry knowledge | Competitive positioning angles |
1.2 Campaign Objective Mapping
Map the business goal to the right campaign objective:
| Business Goal | Campaign Objective | Primary Platform | Ad Format |
|---|---|---|---|
| Brand awareness | Reach / Impressions | Meta, YouTube, TikTok | Video, Display |
| Lead generation | Lead Gen / Conversions | Meta, LinkedIn, Google | Lead forms, Landing pages |
| Trial signups | Conversions | Google, Meta, LinkedIn | Search, Landing pages |
| E-commerce sales | Sales / ROAS | Google Shopping, Meta, TikTok | Shopping, Carousel |
| App installs | App Install | Meta, Google, TikTok | App install ads |
| Event registration | Conversions | Meta, LinkedIn | Event ads, Landing pages |
| Content promotion | Engagement / Traffic | Meta, Twitter, LinkedIn | Boosted posts, Video |
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 · 459 lines · 0 tokens per session scan A f1b9c497437b
market-ads 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 4,089 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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