Vibe_coding_guide: 中文优先的 Vibe Coding / AI coding engineering workflow guide

by Lling0000 · Codex Skill · ★ 237

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Security audit verdict: SAFE · quality 58/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agent-workflowsagentic-engineeringai-agentsai-assisted-developmentai-codingbilingualcodexcoding-agentsdeveloper-productivitydeveloper-tools

Quick Facts

Stars237
Forks23
LanguageJavaScript
CategoryCodex Skill
LicenseMIT
Quality Score58/100
Open Issues4
Last Updated2026-06-25
Created2026-05-05
Platformscodex, node
Est. Tokens~13k

About Vibe_coding_guide

Vibe Coding Guide 把 AI Coding 从 prompt 实验，升级为可审查、可验证、可交付的工程工作流。 语言：中文 | English 在线教程网站 · 中文完整教程 · English Guide · 路线图 中文 PDF · English PDF · 贡献指南 这是什么 AI Coding 如果停留在 prompt 到代码的玩具阶段，很快就会失控：需求模糊但 diff 看起来合理，长会话丢上下文，并行 Agent 相互踩踏，“看起来没问题”替代了真正验证。 Vibe Coding Guide 解决的就是这个断层：把 AI Coding 当成一套工程工作流来管理，从 spec、上下文、计划、实现、review、测试、提交到交接，都要可重复、可审查、可恢复。它不是 prompt 话术合集

Compatible Skills

These tools work well together with Vibe_coding_guide for enhanced workflows:

  • pair-programmer — semantic(0.22)+complementary+rare_topics+same_lang+similar_pop+shared_platform (62%)
  • claude-code — semantic(0.19)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)
  • AI-Code-Tutorials — semantic(0.33)+complementary+rare_topics+similar_pop+shared_platform (61%)
  • vibe-log-cli — semantic(0.33)+complementary+rare_topics+similar_pop+shared_platform (61%)

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  • vibe-log-cli by vibe-log · ⭐ 340

    A CLI tool for logging and analyzing Claude Code and Cursor ai-driven coding session.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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