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 johannesjo · Codex Skill · ★ 1.0k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is parallel-code safe to install? View the security audit →
Ten agents. Ten branches. One afternoon. Dispatch AI coding agents in parallel, each in its own worktree. Review the diffs, merge the wins, toss the rest. Works with Claude Code, Codex, and Gemini · Every change isolated in its own git worktree · Free, open source, no extra platform fee Screenshots |
| Stars | 1,018 |
| Forks | 138 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 67.3530312802563/100 |
| Open Issues | 58 |
| Last Updated | 2026-09-22 |
| Created | 2026-02-18 |
| Platforms | claude-code, cli, codex, gemini, node |
| Est. Tokens | ~16k |
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parallel-code is Run Claude Code, Codex, and Gemini side by side — each in its own git worktree. It is categorized as a Codex Skill with 1.0k GitHub stars.
parallel-code is primarily written in TypeScript. It covers topics such as ai-agents, ai-coding, ai-tools.
You can find installation instructions and usage details in the parallel-code GitHub repository at github.com/johannesjo/parallel-code. The project has 1.0k stars and 138 forks, indicating an active community.
parallel-code is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to parallel-code on Agent Skills Hub include ai-devkit, quint-code, bernstein. 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: