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 enz1m · Codex Skill · ★ 62
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is enzim-coder safe to install? View the security audit →
Enzim Coder Enzim Coder is a GTK4/libadwaita desktop app for working with coding threads, workspaces, Git context, file browsing, and local agent sessions in one place. Today it supports Codex and OpenCode. Soon: Claude Code, Google CLI Multi-chat view Worktrees Remote ✨ Features <td align="ce
| Stars | 62 |
| Forks | 3 |
| Language | Rust |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 68.0251052398679/100 |
| Open Issues | 2 |
| Last Updated | 2026-03-26 |
| Created | 2026-03-12 |
| Platforms | cli, codex, rust |
| Est. Tokens | ~186k |
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enzim-coder is Enzim Coder is a Linux desktop app for working with AI coding threads, workspaces, Git context, file browsing, and agent sessions in one place.. It is categorized as a Codex Skill with 62 GitHub stars.
enzim-coder is primarily written in Rust. It covers topics such as agentic-ai, agentic-coding, agents.
You can find installation instructions and usage details in the enzim-coder GitHub repository at github.com/enz1m/enzim-coder. The project has 62 stars and 3 forks, indicating an active community.
enzim-coder is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to enzim-coder on Agent Skills Hub include code-notify, AgenticGoKit, seance. 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: