awesome-vibe-coding
Centralizes 298+ agent skills and 5,380+ OpenClaw patterns across AI coding tools, reducing time spent searching fragmented resources and enabling faster ado…
298 agent skills (Cursor, Claude Code & Codex), 5,380 OpenClaw skills, 201 ML notebooks, 49 research papers, 15 industry reports for PMs, Designers & Developers.
- Find pre-built agent skills to speed up Cursor or Claude Code implementation
- Access ML notebooks and research papers for data analytics project design
- Retrieve industry reports to support product decisions with current benchmarks
Centralizes 298+ agent skills and 5,380+ OpenClaw patterns across AI coding tools, reducing time spent searching fragmented resources and enabling faster adoption of proven techniques across your development stack.
Data analytics teams and full-stack developers integrating Cursor, Claude Code, or Codex into production workflows.
https://github.com/adriannoes/awesome-vibe-coding
By adriannoes
How to Get It
Not installable — this is a curated resource collection. Browse it at the source link and pull individual skills, notebooks, or reports as needed.
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me find pre-built agent skills to speed up Cursor or Claude Code implementation
Trust Signals Auto-scanned
Community Pulse Growing
Discussed on Hacker News
- A curated list of tools and resources for vibecoders — Hacker News · 5 pts
- Vibe Coding – A Curated List — Hacker News · 3 pts
- Vibe Coding CLI — Hacker News · 2 pts
3 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 42 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 42 GitHub stars; contributors unknown; last commit 0d ago; license MIT.