affiliate-skills and claude-skills-marketplace

These are ecosystem siblings—one provides Claude Skills for marketing automation workflows while the other provides Claude Skills for software engineering workflows, both built on the same Claude Skills framework but targeting distinct professional domains.

affiliate-skills
55
Established
claude-skills-marketplace
51
Established
Maintenance 13/25
Adoption 10/25
Maturity 9/25
Community 23/25
Maintenance 10/25
Adoption 10/25
Maturity 13/25
Community 18/25
Stars: 151
Forks: 70
Downloads:
Commits (30d): 0
Language: HTML
License: MIT
Stars: 463
Forks: 51
Downloads:
Commits (30d): 0
Language: HTML
License: Apache-2.0
No Package No Dependents
No Package No Dependents

About affiliate-skills

Affitor/affiliate-skills

AI-powered Claude Skills for affiliate marketers. Full funnel: research → content → blog → landing → deploy.

Comprises 45 interconnected skills organized across an 8-stage affiliate marketing flywheel (research → content → blog → landing → distribution → analytics → automation → meta), with automatic skill chaining and closed-loop feedback from analytics back to research. Integrates with the Affitor program directory API for live commission and cookie data, and works via text I/O across Claude Code, ChatGPT, Gemini, Cursor, Windsurf, and OpenClaw—installable as native skills or bootstrapped via markdown prompt. Each skill declares suggested next steps and data dependencies, enabling AI agents to autonomously orchestrate multi-stage campaigns from program selection through A/B testing and compliance audits.

About claude-skills-marketplace

mhattingpete/claude-skills-marketplace

Claude Code Skills for software engineering workflows - Git automation, testing, and code review

Based on the README, here's a technical summary: Provides modular Claude Code plugins (Engineering Workflows, Visual Documentation, Code Operations, Productivity Skills) that activate contextually through declarative SKILL.md and AGENT.md files—enabling Git automation, testing, code review, visual diagram generation, and code refactoring without explicit user invocation. Implements the Anthropic code execution pattern via a sandboxed FastMCP server runtime, achieving 90-99% token reduction for bulk operations by executing Python locally rather than processing files through context.

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