No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by inmve · Codex Skill · ★ 348
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-ai-coding-techniques safe to install? View the security audit →
Available Languages: English Português Active Development - Updated November 26, 2025 coding-with-ai.dev Awesome AI Coding Techniques Practical techniques for coding with AI - Community-driven and practitioner-tested This resource organizes techniques for working with coding assistants by development stage (from requirements and planning through review and refactoring). The techniques draw from practitioners including Simon Willison, Armin Ronacher, Indragie Karunaratne, Orta Therox, and the Anthropic team. Community-maintained and living. Contributions welcome. 🚀 Live site: coding-with-ai.dev 📝 Contributing: See CONTRIBUTING.md to share your techniques and experiences Table of Contents Requirements & Planning UI & Prototyping Coding Debugging Testing & QA Review & Refactoring Cross-Stage Techniques Requirements & Planning Set Up Memory Files Create context files that persist
| Stars | 348 |
| Forks | 27 |
| Category | Codex Skill |
| Quality Score | 53.3563376815951/100 |
| Open Issues | 14 |
| Last Updated | 2025-11-26 |
| Created | 2025-08-24 |
| Platforms | claude-code, cli, codex |
| Est. Tokens | ~53k |
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awesome-ai-coding-techniques is Practical techniques for coding with ai assistants (Claude Code, Codex CLI, Cursor, GitHub Copilot, etc). Available in: English • Español • Deutsch • Français • 日本語. It is categorized as a Codex Skill with 348 GitHub stars.
You can find installation instructions and usage details in the awesome-ai-coding-techniques GitHub repository at github.com/inmve/awesome-ai-coding-techniques. The project has 348 stars and 27 forks, indicating an active community.
The top alternatives to awesome-ai-coding-techniques on Agent Skills Hub include awesome-agent-skills, kindly-web-search-mcp-server, holysheep-cli. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: