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 coleam00 · Agent Tool · ★ 13.9k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is context-engineering-intro safe to install? View the security audit →
Context Engineering Template A comprehensive template for getting started with Context Engineering - the discipline of engineering context for AI coding assistants so they have the information necessary to get the job done end to end. Context Engineering is 10x better than prompt engineering and 100x better than vibe coding. 🚀 Quick Start 📚 Table of Contents What is Context Engineering? Template Structure Step-by-Step Guide Writing Effective INITIAL.md Files The PRP Workflow Using Examples Effectively Best Practices What is Context Engineering? Context Engineering represents a paradigm shift from tradi
| Stars | 13,872 |
| Forks | 2,724 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 66.7500726937384/100 |
| Open Issues | 32 |
| Last Updated | 2026-03-16 |
| Created | 2025-07-02 |
| Platforms | claude-code, python |
| Est. Tokens | ~15k |
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context-engineering-intro is Context engineering is the new vibe coding - it's the way to actually make AI coding assistants work. Claude Code is the best for this so that's what this repo is centered around, but you can apply th. It is categorized as a Agent Tool with 13.9k GitHub stars.
context-engineering-intro is primarily written in Python.
You can find installation instructions and usage details in the context-engineering-intro GitHub repository at github.com/coleam00/context-engineering-intro. The project has 13.9k stars and 2724 forks, indicating an active community.
context-engineering-intro is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to context-engineering-intro on Agent Skills Hub include awesome-claude-code, open-saas, notebooklm-skill. 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: