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 YANG-Haruka · Agent Tool · ★ 287
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is LinguaHaru safe to install? View the security audit →
English 日本語 📚 User Guide (Wiki) Next-generation AI translation tool that provides high-quality, precise translations for various common file formats with a single click Supported File Formats 📄 DOCX • 📊 XLSX • 📑 PPTX • 📰 PDF • 📝 TXT • 🎬 SRT • 📘 MD What's This? This translation tool is based on cutting-edge large language models, offering exceptional translation quality with minimal operation, supporting multiple document formats and languages. It provides the following features: Multi-format compatibility: Perfect support for common file formats including .docx, .pptx, .xlsx, .pdf, .txt, .srt, with more document types to be expanded in the future. Global language translation: Covers 10+ languages including Chinese/English/Japanese/Korean/Russian, continuously expanding to meet globalization needs. One-click rapid translatio
| Stars | 287 |
| Forks | 45 |
| Language | Python |
| Category | Agent Tool |
| License | GPL-3.0 |
| Quality Score | 62.3429918486162/100 |
| Last Updated | 2026-09-16 |
| Created | 2024-11-22 |
| Platforms | cli, python |
| Est. Tokens | ~14k |
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LinguaHaru is Next-Gen AI Translation Tool Powered by LLM. Support Office documents, PDF, TXT, and more format with just one click.. It is categorized as a Agent Tool with 287 GitHub stars.
LinguaHaru is primarily written in Python.
You can find installation instructions and usage details in the LinguaHaru GitHub repository at github.com/YANG-Haruka/LinguaHaru. The project has 287 stars and 45 forks, indicating an active community.
LinguaHaru is released under the GPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to LinguaHaru on Agent Skills Hub include awesome-android-agent-skills, synalinks-skills, agent-skills. 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: