by nekocode · Agent Tool · ★ 280
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
npm install -g agent-worktree
Taken from the project's README on GitHub.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 280 |
| Forks | 18 |
| Language | Rust |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 79/100 |
| Last Updated | 2026-10-20 |
| Created | 2026-02-05 |
| Platforms | rust |
| Est. Tokens | ~23k |
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,...
Looking for a agent-worktree alternative? If you're comparing agent-worktree with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
A dev environment for AI agents.
Bring order to your projects, environments, and day-to-day work.
Give git-like & traceable memory to OpenClaw and any coding agents. By https://memov.ai/ aka Entire CLI for ev
A desktop MCP client designed as a tool unitary utility integration, accelerating AI adoption through the Mode
he just wants to help-pi!
Ultimate Context Engineering Infrastructure, starting from MCPs and Integrations
Explore other popular agent tool tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: