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 NextWeb4 · Agent Tool · ★ 167
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is deepseek-translation-studio safe to install? View the security audit →
DeepSeek Translation Studio A Windows PySide6 workspace for DeepSeek API/Web translation, long SRT continuation, visible-answer capture, history, export, and distributable desktop packaging. The repository also builds DeepSeek Conversation Capture, a stripped standalone edition for everyday DeepSeek Web prompts and visible-answer capture. Two Desktop Applications DeepSeek Translation Studio PySide6 workspace wit
| Stars | 167 |
| Forks | 4 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 68.9511567354593/100 |
| Last Updated | 2026-07-30 |
| Created | 2026-07-07 |
| Platforms | browser, python |
| Est. Tokens | ~16k |
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deepseek-translation-studio is Windows Python/PySide6 translation studio for DeepSeek Web/API workflows, SRT continuation, capture, and packaging.. It is categorized as a Agent Tool with 167 GitHub stars.
deepseek-translation-studio is primarily written in Python. It covers topics such as ai-tools, deepseek, desktop-app.
You can find installation instructions and usage details in the deepseek-translation-studio GitHub repository at github.com/NextWeb4/deepseek-translation-studio. The project has 167 stars and 4 forks, indicating an active community.
The top alternatives to deepseek-translation-studio on Agent Skills Hub include web-agent-protocol, LovelyAIMaster, mcp-nixos. 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: