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 EdgeTypE · Agent Tool · ★ 487
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is better-deepseek safe to install? View the security audit →
Better DeepSeek Better DeepSeek is a browser extension that enhances the DeepSeek chat interface with a powerful set of tools, persistent memory, and a customizable system prompt. It enables DeepSeek to generate files, run code, create presentations, and manage complex projects directly within the conversatio
| Stars | 487 |
| Forks | 56 |
| Language | JavaScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 72.5442826343233/100 |
| Open Issues | 10 |
| Last Updated | 2026-09-19 |
| Created | 2026-04-12 |
| Platforms | browser, node |
| Est. Tokens | ~19k |
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better-deepseek is A powerful browser extension that supercharges DeepSeek Chat with custom tooling, persistent memory, and seamless project scaffolding. Generate and download files, run Python in-browser, create PowerP. It is categorized as a Agent Tool with 487 GitHub stars.
better-deepseek is primarily written in JavaScript. It covers topics such as ai-tools, automation, browser-extension.
You can find installation instructions and usage details in the better-deepseek GitHub repository at github.com/EdgeTypE/better-deepseek. The project has 487 stars and 56 forks, indicating an active community.
better-deepseek is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to better-deepseek on Agent Skills Hub include ctxport, vibe-annotations, claudekit. 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: