Awesome-Vibecoding-Guide and awesome-vibe-coding

These two tools are complements, as one is a guide compiled from real commercial projects and AI-assisted code, while the other is a hand-picked collection of tools and resources for the same domain, suggesting they could be used in conjunction for both learning and practical application.

Awesome-Vibecoding-Guide
51
Established
awesome-vibe-coding
46
Emerging
Maintenance 10/25
Adoption 10/25
Maturity 13/25
Community 18/25
Maintenance 6/25
Adoption 10/25
Maturity 8/25
Community 22/25
Stars: 494
Forks: 59
Downloads:
Commits (30d): 0
Language:
License: MIT
Stars: 614
Forks: 94
Downloads:
Commits (30d): 0
Language:
License:
No Package No Dependents
No License No Package No Dependents

About Awesome-Vibecoding-Guide

loppety/Awesome-Vibecoding-Guide

A compendium drawn from real commercial projects and hundreds of thousands of lines of AI‑assisted code. Read it end‑to‑end or feed this repo to your AI agent for summaries and Q&A. Stars and watches appreciated! ⭐

Operationalizes AI-assisted development into three distinct revenue models—local business websites ($300-700 per project), workflow automations ($500-3000+), and micro-SaaS tools—with production-ready delivery systems covering phase-based workflows, quality standards, and LLM prompting techniques. Built on a minimal stack (Astro, Tailwind, Cloudflare Pages/Workers) with cost-effective model providers (Synthetic.new, MiniMax, GLM) and coding agents, emphasizing that methodology matters more than which LLM you choose. Includes cross-cutting guidance on git safety, accessibility/SEO, troubleshooting, and client acquisition strategies alongside reference implementations and cheat sheets.

About awesome-vibe-coding

ai-for-developers/awesome-vibe-coding

A hand-picked collection of tools and resources for Vibe Coding

Organizes AI-assisted development tools across web builders, editors, CLI agents, and plugins—spanning full-stack generators like Bolt.new and Cursor down to terminal assistants like aider. The collection emphasizes prompt-driven workflows where developers describe intent rather than write traditional code, supported by LLM-powered task decomposition and real-time collaboration features. Targets modern development stacks including React, Firebase, and AWS, with integrations for popular IDEs, version control, and local model frameworks.

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