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 bahayonghang · Codex Skill · ★ 276
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is drawio-skills safe to install? View the security audit →
Draw.io Skill for Claude, Gemini & Codex Important: Draw.io Skill 2.2.0 is a YAML-first, offline-first base workflow. The default path is local generation through , optionally enhanced by draw.io Desktop for PNG/PDF/JPG and embedded SVG export. The next-ai-draw-io MCP server () is optional live refinement for the base skill only, not a hard dependency. English Documentation Draw.io Skill is a YAML-first draw.io authoring system for engineering diagrams, network diagrams, structured redraws, Mermaid/CSV conversion, and imported files. Publication-facing work is handled by an Academic Overlay that depends on the sibling base skill instead of copying its runtime. Skill Variants : Draw.io Base Skill. Owns the shared CLI, schemas, referen
| Stars | 276 |
| Forks | 16 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 70.6221108541714/100 |
| Last Updated | 2026-08-24 |
| Created | 2025-12-26 |
| Platforms | codex, node |
| Est. Tokens | ~15k |
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drawio-skills is drawio skills for cc,codex. It is categorized as a Codex Skill with 276 GitHub stars.
drawio-skills is primarily written in JavaScript. It covers topics such as drawio, skills.
You can find installation instructions and usage details in the drawio-skills GitHub repository at github.com/bahayonghang/drawio-skills. The project has 276 stars and 16 forks, indicating an active community.
drawio-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to drawio-skills on Agent Skills Hub include rulesync, douyin-mcp-server, ios-simulator-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: