Open Source Skill for Parallel AI Coding Agents with Human Gate

A Reddit user posted an open-source skill definition (a markdown file) for running parallel AI coding agents with a human-in-the-loop gate before production. The skill targets developers using Claude Code, Codex, Cursor, or any LLM that reads markdown. It solves the post-parallel merge problem: how to validate multiple features together, run smoke tests, and ensure nothing hits production without explicit approval.

How It Works

Three agents work simultaneously, each in its own git worktree to avoid conflicts. The skill then automates the full pipeline:

• Parallel workers — each agent works on a separate feature branch.
• Integration branch — all feature branches merge into an integration branch for combined validation.
• Type/build validation — runs type checking and build steps on the integration branch.
• Runtime smoke tests — executes a quick smoke test suite.
• Staging promotion — if smoke tests pass, promotes to staging.
• Hard human gate — requires manual approval before merging to main.

Every feature uses a --no-ff merge so individual features can be reverted without affecting others.

Installation

To install, paste this prompt to your LLM:

Read the SKILL.md file from https://github.com/knods-io/parallel-agents-skill and adapt it to our project. Keep the core flow and the mythological worker names, but tailor everything to how we actually work. Then install it as a skill in this project.

The repo is at github.com/knods-io/parallel-agents-skill. It's not a library or package — just a markdown file you give to your LLM. The author asks for feedback on what's missing, what would break in different setups, and what others would change.

Who It's For

Developers using Claude Code or similar AI coding agents who want to scale feature development with parallel agents while maintaining safety checks before production deployment.