ralph-loop-integration

Wrap IR-v2 reasoning patterns in completion-promise gated loops with checkpointed persistence.

4|1|Updated Jan 19, 2026
One-click install
npx skills add https://github.com/kimasplund/claude_cognitive_reasoning --skill ralph-loop-integration
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ralph-loop-integration
Source: https://github.com/kimasplund/claude_cognitive_reasoning/tree/main/cognitive-skills/ralph-loop-integration
Command: npx skills add https://github.com/kimasplund/claude_cognitive_reasoning --skill ralph-loop-integration

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a persistent iteration wrapper that coordinates multiple IR-v2 reasoning patterns through completion-promise gated loops, enabling high-confidence results.

Core Features & Use Cases

  • Persistent session: Maintains iteration state across multiple reasoning passes using Ralph-Loop.
  • Pattern handover: Safely switches between BoT, ToT, AR, and other patterns with documented context.
  • Checkpointed execution: Supports long-running tasks with checkpoints and resume capability.

Quick Start

Invoke a Ralph-Loop wrapped IR-v2 orchestration to progressively refine answers. Example: run BoT → ToT → AR, with a final confirmation when confidence exceeds 90%.

Frequently Asked Questions about ralph-loop-integration

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

FAQPage Schema
How do I maintain reasoning state across multiple iteration passes for long-running analysis?

Persistent iteration wraps multiple reasoning patterns in completion-promise gated loops, maintaining session state across passes so long-running analyses can refine progressively until high confidence is achieved.

What is pattern handover in iterative cognitive reasoning?

Pattern handover safely switches between reasoning patterns like BoT, ToT, and AR during iteration, preserving documented context so each pattern receives coherent state from the previous one without loss.

How do I checkpoint long-running reasoning tasks so I can resume later?

Checkpointed execution saves iteration state at defined points during reasoning loops, enabling resume capability so long-running analyses can continue from the last checkpoint rather than restarting.

Can I orchestrate multiple reasoning patterns in a single loop for high-confidence results?

Yes, multi-pattern orchestration chains patterns such as BoT, ToT, and AR within completion-promise gated loops, running sequential passes with a final confirmation when confidence exceeds a defined threshold.

Do I need the Ralph-Loop plugin environment to run IR-v2 pattern orchestration?

Yes, the Ralph-Loop plugin environment is required to execute IR-v2 orchestration with pattern handover and checkpoint management, providing the persistent iteration wrapper that gates loop completion.