# 2025Emma/vibe-coding-cn

Repository: https://github.com/2025Emma/vibe-coding-cn
Canonical: https://ross.abutalabs.com/products/vibe-coding-cn
Language: Python
License: MIT
License Family: permissive
Last push: 2025-12-17T00:11:18+00:00

## Health v2 (maintenance only)
Score: 42/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 57, release rhythm 35, longevity 18
- inputs: {"age_days": 260, "days_push": 260, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 22802, forks 2406 (observed 2026-08-28T04:11:34.109877+00:00)

## What it is
A multilingual guide and workstation for 'vibe coding' — building software by pair programming with AI assistants. It curates practices, workflows, and resources for turning ideas into working code through natural-language collaboration with LLMs.

## Use cases
- learn how to build apps by prompting AI coding assistants
- find best practices for AI pair programming
- get started with vibe coding as a beginner
- improve my workflow when coding with LLMs
- learn prompt techniques for software development
- find a structured guide to AI-assisted development

## When to choose
- you want a curated, community-maintained guide to AI-assisted coding
- you are new to building software with LLM assistants and want structured learning material
- you need multilingual documentation on vibe coding practices

## When to avoid
- you need a runnable tool, library, or framework rather than a guide
- you want formal training or certification rather than community documentation
- you need project-specific engineering documentation

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, developer-tools, prompt-engineering
- domain: artificial-intelligence, large-language-models, tutorials, developer-tools, awesome-lists
- platform: cross-platform
- tags: vibe-coding, ai-pair-programming, guide, multilingual, llm-collaboration

## Member repositories
- 2025Emma/vibe-coding-cn (main) score 42

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:34.109877+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:56:55.162277+00:00, confidence not recorded.
  - readme: https://github.com/2025Emma/vibe-coding-cn (fetched 2026-08-28T04:11:34.109877+00:00, sha 3ca8cb60cde0)
- Data as of 2026-08-30T08:39:29.467469+00:00.