Orchestrate parallel Claude task execution with git worktrees and tmux windows.
npx skills add https://github.com/shonenm/dotfiles --skill ralph-parallel
Please help me install this Agent Skill. Skill: ralph-parallel Source: https://github.com/shonenm/dotfiles/tree/main/common/claude/.claude/skills/ralph-parallel Command: npx skills add https://github.com/shonenm/dotfiles --skill ralph-parallel
This Skill orchestrates parallel execution of tasks defined in a state file or task list, managing dependencies and providing visibility into each task's progress.
Execute the ralph-parallel skill to process tasks from the default state file.
High-intent search queries and answers about installing and using this skill.
You can run parallel Claude processes by defining tasks in a state file or task list. The Skill orchestrates up to four concurrent Claude processes, analyzing dependencies to ensure correct execution order.
Dependency analysis for parallel task execution works by parsing a task graph from your state file to determine execution order. This ensures dependent tasks wait, while independent tasks run concurrently in isolated environments.
Yes, git worktree and tmux are required to monitor parallel task execution. Each independent Claude process runs in an isolated git worktree and tmux window, allowing real-time observation of task status and progress.
The best way to manage multiple AI agents is breaking complex feature development into smaller independent tasks. The Skill manages their execution, allowing agents to work simultaneously with progress visible in separate terminal windows.
Yes, Bash and Task tools are supported alongside Read, Write, Glob, and Grep for orchestrating task execution. These dependencies enable the Skill to process state files, analyze dependencies, and manage parallel Claude processes.
Parallel task execution limits concurrent processes to four to balance resource usage and performance. This constraint allows independent Claude processes to run simultaneously without overwhelming system resources while maintaining real-time visibility.
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