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marketing-skills

Generate marketing assets and strategies using standard-library Python tools.

1|Updated Mar 18, 2026
Search Tags:#seo#content-creation#brand-voice#cro#ai-marketing#campaign-analytics
One-click install
npx skills add https://github.com/xxih/ai-harness-zh --skill marketing-skills-xxih
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: marketing-skills
Source: https://github.com/xxih/ai-harness-zh/tree/main/references/translations/alirezarezvani-claude-skills/marketing-skill
Command: npx skills add https://github.com/xxih/ai-harness-zh --skill marketing-skills-xxih

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Marketing teams struggle to quickly generate high‑quality content, optimize for search, improve conversion rates, and coordinate campaigns across multiple channels without fragmented tools.

Core Features & Use Cases

  • Foundation Context: Shared marketing-context.md provides brand voice, audience personas, and competitive landscape for all skills.
  • Orchestration Router: marketing-ops routes requests to the appropriate pod (content, SEO, CRO, channels, growth, intelligence, sales).
  • Specialized Pods: Each pod offers focused capabilities such as AI‑enhanced SEO, content humanization, CRO recommendations, ad‑creative validation, growth experiment design, competitor analysis, and pricing strategy.
  • Zero‑Dependency Python Tools: 27 standard‑library scripts enable tasks like content scoring, brand voice analysis, ad copy validation, and pricing modeling without installing extra packages.
  • Use Case Example: An agency can automatically generate a SEO‑optimized blog post, refine its tone to match brand guidelines, and produce associated social media snippets in a single workflow.

Quick Start

Ask the agent to create a SEO‑optimized blog post about sustainable travel using the marketing‑ops router.

Frequently Asked Questions about marketing-skills

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate SEO-optimized content and marketing assets using AI?▼

You generate SEO-optimized content by routing requests through an AI-driven marketing-ops router that coordinates specialized pods for content creation, brand voice analysis, and SEO optimization. This shared context approach ensures targeted assets align with audience personas.

What's the best way to align AI-generated marketing copy with my brand voice?▼

To align AI copy with your brand voice, the system uses a shared marketing-context file containing brand guidelines and audience data. Specialized pods then analyze and refine generated content to ensure tone consistency across all marketing channels.

Do I need external Python packages to run these AI marketing workflows?▼

No, you do not need external Python packages to run these AI marketing workflows. The skill operates using 27 zero-dependency standard-library Python scripts for tasks like content scoring, ad copy validation, and pricing modeling.

Can I design growth experiments and analyze competitive landscapes without fragmented tools?▼

Yes, you can design growth experiments and analyze competitive landscapes using specialized pods for intelligence analysis. These pods consolidate campaign analytics and competitor research into a single coordinated workflow without fragmented tools.

How do I improve conversion rate optimization for multi-channel ad campaigns?▼

You improve conversion rate optimization by applying CRO recommendations and ad-creative validation through specialized pods. The system analyzes campaign analytics to suggest enhancements tailored to your specific channel strategies.

When should I not use a shared marketing-context file for content creation?▼

You should not use a shared marketing-context file if your campaigns require entirely isolated brand voices or lack defined audience personas. The system relies on this centralized context to accurately route and humanize content.

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