Is running Ralph Guide safe for my codebase?

Since Ralph runs with the --dangerously-skip-permissions flag to maintain autonomy, it is highly recommended to run the workflow inside a Docker container or a dedicated VM.

Does Ralph Guide require any external dependencies?

Yes, Ralph Guide requires Claude Code, the Beads Git-backed issue tracker, and jq for processing JSON output.

Can I run multiple Ralph agents at the same time?

Yes, Ralph is designed for parallel execution. Multiple terminal instances can run the loop simultaneously, and they will safely claim different tasks from the queue without duplication.

How does the 'Harvest' phase work?

The Harvest phase scans task comments for tags like [LEARNING] or [GAP] and automatically generates artifacts like CLAUDE.md updates, new documentation, or follow-up tasks.

What is the Ralph loop in Claude Code?

The Ralph loop is an autonomous execution cycle where agents claim tasks from a Git-backed queue, implement changes, verify them against tests, and commit the results without manual intervention.

Ralph Workflow Automation

Name: Ralph Workflow Automation
Author: mj-meyer

bymj-meyer

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Productivity & Workflow

Automates multi-step development cycles through structured task specifications and autonomous parallel agent loops.

About

Ralph Guide is a comprehensive framework for Claude Code designed to manage complex development lifecycles using the 'Choo Choo Ralph' methodology. It enables users to transform high-level project plans into structured, reviewable specifications that are then 'poured' into a Git-backed issue tracker called Beads. Once tasks are initialized, the skill facilitates autonomous execution through parallelized Ralph loops, which handle implementation, verification, and error recovery. The process concludes with a unique 'Harvest' phase that extracts architectural patterns, technical debt, and project gaps directly from agent activity into persistent documentation.

Key Features

Iterative Plan-to-Spec transformation with built-in AI review cycles
Learning extraction system to capture architectural insights and project gaps
Git-backed task persistence and state management using Beads
Automated error handling with health checks and intelligent rework loops
9 GitHub stars
Autonomous execution loop with support for multiple parallel agents

Use Cases

Automating the creation of project-specific documentation and coding standards from agent logs
Scaling complex feature development by delegating tasks to multiple autonomous agents
Managing large-scale refactorings that require consistent verification and safety checks

About

Key Features

Iterative Plan-to-Spec transformation with built-in AI review cycles
Learning extraction system to capture architectural insights and project gaps
Git-backed task persistence and state management using Beads
Automated error handling with health checks and intelligent rework loops
9 GitHub stars
Autonomous execution loop with support for multiple parallel agents

Use Cases

Automating the creation of project-specific documentation and coding standards from agent logs
Scaling complex feature development by delegating tasks to multiple autonomous agents
Managing large-scale refactorings that require consistent verification and safety checks