Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by am-will · Agent Tool · ★ 81
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is snag safe to install? View the security audit →
Snag Beta - This tool is in active development. If you encounter any issues, please report them. Screenshot-to-text CLI tool powered by vision AI (Google Gemini, OpenRouter, or Z.AI). Capture any region of your screen and instantly get a markdown description in your clipboard - ready to paste into an LLM, document, or anywhere else. Features Region selection - Click and drag to capture any part of your screen Multi-monitor support - Works across all your displays Smart transcription - Handles text, code, diagrams, charts, UI elements, and images Instant clipboard - Results copied automatically, ready to paste Multiple providers - Google Gemini, OpenRouter, or Z.AI (GLM-4.6V) Cross-platform - Linux (X11/Wayland), Windows, macOS Installation Linux Dependencies X11: Wayland: macOS Permissions On first run, macOS will prompt for Screen Recording permissions: Grant permission when prompted Restart the app (required for permissions to take effect) On second ru
| Stars | 81 |
| Forks | 11 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 71.4379550143465/100 |
| Last Updated | 2026-01-11 |
| Created | 2026-01-09 |
| Platforms | cli, gemini, python |
| Est. Tokens | ~7k |
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snag is Screenshot-to-text CLI tool powered by Google Gemini vision. It is categorized as a Agent Tool with 81 GitHub stars.
snag is primarily written in Python.
You can find installation instructions and usage details in the snag GitHub repository at github.com/am-will/snag. The project has 81 stars and 11 forks, indicating an active community.
snag is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to snag on Agent Skills Hub include tutor-skills, repren. 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: