claude-code-skill-factory and claude-skills-marketplace

Project A is a toolkit for building Claude Skills, while project B is a collection of specific Claude Skills for software engineering workflows, making them complementary where B could potentially be built using A.

Maintenance 6/25
Adoption 10/25
Maturity 13/25
Community 24/25
Maintenance 10/25
Adoption 10/25
Maturity 13/25
Community 18/25
Stars: 591
Forks: 114
Downloads:
Commits (30d): 0
Language: Python
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 claude-code-skill-factory

alirezarezvani/claude-code-skill-factory

Claude Code Skill Factory — A powerful open-source toolkit for building and deploying production-ready Claude Skills, Code Agents, custom Slash Commands, and LLM Prompts at scale. Easily generate structured skill templates, automate workflow integration, and accelerate AI agent development with a clean, developer-friendly setup.

Provides interactive guided agents and slash commands that streamline skill/agent/hook generation through templated Q&A workflows, with built-in validation and packaging. Integrates with Claude Code's native skill system and Codex CLI via automatic CLAUDE.md↔AGENTS.md translation, while offering 69 pre-built prompt presets across 15 professional domains accessible as an installable skill.

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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