awesome-skills and claude-superskills

awesome-skills
42
Emerging
claude-superskills
35
Emerging
Maintenance 13/25
Adoption 4/25
Maturity 11/25
Community 14/25
Maintenance 10/25
Adoption 5/25
Maturity 20/25
Community 0/25
Stars: 7
Forks: 3
Downloads:
Commits (30d): 0
Language: Shell
License:
Stars: 12
Forks:
Downloads:
Commits (30d): 0
Language: JavaScript
License: MIT
No Package No Dependents
No risk flags

About awesome-skills

theneoai/awesome-skills

🌟 450+ Expert AI Skills | CEO, Doctor, Engineer, Scientist & more | Multi-platform: Claude, Cursor, Codex, Kimi, OpenClaw | Transform AI into any professional

Implements a dual-track validation system (text analysis + runtime execution) with a 6-dimension quality rubric to certify skills to 9.5/10 standards, differentiating it from static skill libraries. The architecture uses progressive disclosure—compact skill files paired with on-demand reference directories—reducing token overhead by 50% while organizing 967 skills across 60 professional domains with tiered complexity (Lite/Standard/Enterprise). Integrates with Claude, Cursor, and other LLM platforms through standardized YAML metadata and a skill-manager CLI for automated evaluation and restoration workflows.

About claude-superskills

ericgandrade/claude-superskills

44+ Universal AI Skills for Claude Code & GitHub Copilot. Standardized workflows for Solution Architecture, Startup Strategy, Software Engineering, and Product Growth.

Provides 46+ modular skills accessible via standardized CLI commands and native Claude Code plugin integration, with platform-aware installation that auto-detects environments and manages version differences across 8 AI coding assistants. Uses a namespace-based skill discovery system (`/claude-superskills:skill-name`) and supports multiple installation paths including zero-dependency local installation, global npm, and custom plugin uploads for Claude Desktop Cowork. Skills span solution architecture, startup strategy, software engineering, product growth, and career development—each versioned independently and bundled for selective installation.

Scores updated daily from GitHub, PyPI, and npm data. How scores work