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 AsyncFuncAI · Codex Skill · ★ 17.9k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is deepwiki-open safe to install? View the security audit →
DeepWiki-Open (Grok-Wiki) DeepWiki is my own implementation attempt of DeepWiki, automatically creates beautiful, interactive wikis for any GitHub, GitLab, or BitBucket repository! Just enter a repo name, and DeepWiki will: Analyze the code structure Generate comprehensive documentation Create visual diagrams to explain how everything works Organize it all into an easy-to-navigate wiki English Русский Deepwiki-Open 2.0 (Grok Wiki is now live) Download at https://grok-wiki.com https://github.com/user-attachments/assets/48d1e60a-eb91-4c05-a5a8-3624ffb79fb1 🤝 C
| Stars | 17,877 |
| Forks | 1,998 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 53.6803446894209/100 |
| Open Issues | 267 |
| Last Updated | 2026-09-03 |
| Created | 2025-04-30 |
| Platforms | cli, codex, gemini, python |
| Est. Tokens | ~13k |
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deepwiki-open is Open Source DeepWiki: AI-Powered Wiki Generator for GitHub/Gitlab/Bitbucket Repositories. Join the discord: https://discord.gg/gMwThUMeme. It is categorized as a Codex Skill with 17.9k GitHub stars.
deepwiki-open is primarily written in Python. It covers topics such as ai, codex, gemini.
You can find installation instructions and usage details in the deepwiki-open GitHub repository at github.com/AsyncFuncAI/deepwiki-open. The project has 17.9k stars and 1998 forks, indicating an active community.
deepwiki-open is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to deepwiki-open on Agent Skills Hub include dyad, ai-guide, codecompanion.nvim. 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: