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 LeanBitLab · Agent Tool · ★ 172
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is HeliboardL safe to install? View the security audit →
LeanType LeanType is a fork of HeliBoard - a privacy-conscious and customizable open-source keyboard based on AOSP/OpenBoard. This fork adds optional AI-powered features using Gemini, Groq, and OpenAI-compatible APIs, offering a hybrid experience: a private, offline core with opt-in cloud intelligence. What's New in LeanType 🤖 Multi-Provider AI - Proofread using Gemini, Groq (Llama 3, Mixtral), or OpenAI-compatible providers. Supports dynamic fetching of latest models directly from providers. 🛡️ Offline AI - Private, on-device proofreading and translation using ONNX models (Offline build only). 🌐 AI Translation - Translate selected text directly using your chosen AI provider, with a separate model selector. [🧠 Custom AI Keys
| Stars | 172 |
| Forks | 6 |
| Language | Java |
| Category | Agent Tool |
| License | GPL-3.0 |
| Quality Score | 58.1013390917066/100 |
| Open Issues | 6 |
| Last Updated | 2026-03-04 |
| Created | 2026-01-15 |
| Platforms | gemini, java |
| Est. Tokens | ~23477k |
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HeliboardL is LeanType is an Open-source, AI-enhanced keyboard fork of HeliBoard with customizable AI providers and dedicated AI keys.. It is categorized as a Agent Tool with 172 GitHub stars.
HeliboardL is primarily written in Java. It covers topics such as ai-tools, android, aosp.
You can find installation instructions and usage details in the HeliboardL GitHub repository at github.com/LeanBitLab/HeliboardL. The project has 172 stars and 6 forks, indicating an active community.
HeliboardL is released under the GPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to HeliboardL on Agent Skills Hub include Deskdrop, PixelBoard, ctxport. 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: