factory-ralph-loop

Repeatedly run an agent until tasks complete using filesystem-backed state.

19|3|Updated Feb 4, 2021
One-click install
npx skills add https://github.com/laulauland/dotfiles --skill factory-ralph-loop
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: factory-ralph-loop
Source: https://github.com/laulauland/dotfiles/tree/main/shared/.pi/agent/extensions/pi-factory/skills/factory-ralph-loop
Command: npx skills add https://github.com/laulauland/dotfiles --skill factory-ralph-loop

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates iterative problem solving by repeatedly running an agent until a task is complete, using the filesystem as persistent memory to retain changes across iterations.

Core Features & Use Cases

  • Filesystem-backed state: preserves progress and artifacts between iterations.
  • Deterministic prompts: reuses the same instruction set to improve consistency.
  • Clear exit conditions: stops when success criteria (tests pass, lint clean, or tasks exhausted) are met.
  • Simple orchestration: a single loop that repeatedly invokes the agent until completion.
  • Common use cases: fix lint errors, pass test suites, or finish PRD-driven work in a codebase.

Quick Start

Run the Ralph Loop on your project and iteratively fix issues until all tasks are complete, with filesystem memory persisting across iterations.

Frequently Asked Questions about factory-ralph-loop

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate lint fixing and test suite completion with persistent memory across iterations?

Automate iterative lint fixing and test completion by running an agent in a loop that uses the filesystem as persistent memory, retaining code changes and progress until all success criteria are met.

What is the best way to iteratively finish PRD-driven work in a codebase using an automated agent?

Iterative PRD-driven work is automated by repeatedly invoking an agent with deterministic prompts and a simple loop orchestrator, using filesystem-backed state to preserve artifacts until tasks are exhausted.

How does an agent loop use filesystem-backed state to automate repetitive software tasks?

An agent loop uses filesystem-backed state by writing progress and artifacts to the filesystem between iterations, ensuring the agent retains context and changes across repetitive runs without losing data.

Can I use a simple loop orchestrator to control agent iterations for repetitive codebase tasks?

Yes, a simple loop orchestrator controls agent iterations by repeatedly invoking the agent with deterministic prompts and checking explicit exit conditions like passing tests or clean lint results.

When do I need explicit exit conditions for an iterative agent loop in software engineering?

Explicit exit conditions are needed when an iterative agent loop must stop automatically upon meeting success criteria, such as when all tests pass, lint is clean, or PRD-driven tasks are fully exhausted.

Does the Ralph Loop work without external dependencies to automate iterative problem solving?

The Ralph Loop operates without external dependencies, relying solely on the filesystem for persistent memory and a simple orchestrator to control automated iterative problem solving until exit conditions are met.