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 migsilva89 · Agent Tool · ★ 97
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is imark safe to install? View the security audit →
Imark ® Native Markdown reader for macOS. Double-click a .md file and it opens rendered, reloads itself while you edit, and previews in the Finder with the space bar. Comment on a phrase and the note goes into the file itself. Nothing leaves the machine. Comment on anything. The note goes into the .md<
| Stars | 97 |
| Forks | 8 |
| Language | Swift |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 64.0573025255877/100 |
| Open Issues | 1 |
| Last Updated | 2026-10-11 |
| Created | 2026-08-05 |
| Platforms | claude-code |
| Est. Tokens | ~19k |
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imark is Native Markdown reader for macOS. Keep it open while you write and it follows every save. Comment on a phrase and the note is saved into the .md file itself. Your coding agent can open a plan here and. It is categorized as a Agent Tool with 97 GitHub stars.
imark is primarily written in Swift. It covers topics such as ai-agents, annotations, appkit.
You can find installation instructions and usage details in the imark GitHub repository at github.com/migsilva89/imark. The project has 97 stars and 8 forks, indicating an active community.
imark is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to imark on Agent Skills Hub include Usage4Claude, Hopet, dotfiles. 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: