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 froggeric · Agent Tool · ★ 67
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is gemini-watermark-and-synthid-remover safe to install? View the security audit →
wmr: Watermark Remover is a command-line tool that removes visible watermarks from images and videos made by Google Gemini, Veo, and NotebookLM, and can scrub the invisible SynthID watermark through lossy SDXL regeneration. Every release package is a single self-contained binary that runs on a clean system with nothing to install. macOS builds are Developer ID signed and Apple-notarized, so they pass Gatekeeper with no extra steps. Table of contents What it does Quick start Usage reference Common flags Still-image geometry [SynthID (invisible watermark)](#synthid-invisibl
| Stars | 67 |
| Forks | 14 |
| Language | C++ |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 65.9344842913006/100 |
| Last Updated | 2026-09-14 |
| Created | 2026-05-28 |
| Platforms | cli, gemini |
| Est. Tokens | ~25k |
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gemini-watermark-and-synthid-remover is Cross platform CLI tool for removing watermarks from images and videos generated by Google Gemini, Veo, and NotebookLM.. It is categorized as a Agent Tool with 67 GitHub stars.
gemini-watermark-and-synthid-remover is primarily written in C++. It covers topics such as c2pa, cli, coreml.
You can find installation instructions and usage details in the gemini-watermark-and-synthid-remover GitHub repository at github.com/froggeric/gemini-watermark-and-synthid-remover. The project has 67 stars and 14 forks, indicating an active community.
gemini-watermark-and-synthid-remover is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to gemini-watermark-and-synthid-remover on Agent Skills Hub include code-notify, gemini-watermark-remover, os-ai-computer-use. 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: