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 funador · Claude Skill · ★ 124
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is claude-code-merge-queue safe to install? View the security audit →
Claude Code Merge Queue 🚦 The local, zero-cost merge queue for parallel Claude Code agents. Several agents land, build, and test at the same time — this serializes it so push races, redundant heavy builds, and shared-resource test flakiness can't happen. ⚡ Quickstart Contents [⚙️ Configu
| Stars | 124 |
| Forks | 4 |
| Language | TypeScript |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 68.5758105379259/100 |
| Last Updated | 2026-08-24 |
| Created | 2026-07-10 |
| Platforms | claude-code, node |
| Est. Tokens | ~15k |
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claude-code-merge-queue is The local merge queue for parallel Claude Code agents. It is categorized as a Claude Skill with 124 GitHub stars.
claude-code-merge-queue is primarily written in TypeScript. It covers topics such as ai-agents, claude-code, coding-agent.
You can find installation instructions and usage details in the claude-code-merge-queue GitHub repository at github.com/funador/claude-code-merge-queue. The project has 124 stars and 4 forks, indicating an active community.
claude-code-merge-queue is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to claude-code-merge-queue on Agent Skills Hub include garcon, smart-ralph, AppGenesisForge. 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: