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 nekocode · Agent Tool · ★ 274
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agent-worktree safe to install? View the security audit →
agent-worktree A Git worktree workflow tool for AI coding agents. Enables parallel development with isolated environments. 中文文档 Why AI coding agents work best with isolated environments: Parallel execution: Run multiple agents simultaneously without interference Clean separation: Each feature gets its own working directory Snap mode: "Use and discard" workflow — create worktree, run agent, merge, cleanup Install Update to the latest version: Shell integration is installed automatically. To reinstall manually: Supported shells: bash, zsh, fish, PowerShell Quick Start Other useful commands: Snap Mode One-liner for AI agent workflows: bash wt new -s claude # Random branch name wt new fix-bug -s codex # Specified branch name wt new -s "claude --dangerously-skip-permissions" # Comm
| Stars | 274 |
| Forks | 18 |
| Language | Rust |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 78.89885549603/100 |
| Last Updated | 2026-08-25 |
| Created | 2026-02-05 |
| Platforms | rust |
| Est. Tokens | ~23k |
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agent-worktree is A Git worktree workflow tool for AI coding agents. Enables parallel development with isolated environments.. It is categorized as a Agent Tool with 274 GitHub stars.
agent-worktree is primarily written in Rust. It covers topics such as agent, ai, git.
You can find installation instructions and usage details in the agent-worktree GitHub repository at github.com/nekocode/agent-worktree. The project has 274 stars and 18 forks, indicating an active community.
agent-worktree is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to agent-worktree on Agent Skills Hub include jean, aizen, memov. 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: