ralph

Orchestrate persistent parallel task execution with architect verification and automatic retries.

1|Updated Sep 22, 2025
One-click install
npx skills add https://github.com/prthik/prathik-astro --skill ralph-prthik
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ralph
Source: https://github.com/prthik/prathik-astro/tree/main/.codex/skills/ralph
Command: npx skills add https://github.com/prthik/prathik-astro --skill ralph-prthik

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Ralph provides a persistence loop that keeps working on a task until it is fully complete and architect-verified, preventing silent failures and incomplete deliveries.

Core Features & Use Cases

  • Automated parallel execution with session persistence and automatic retry on failure.
  • Mandatory architect verification before declaring completion.
  • Suitable for long-running, multi-step tasks that require durable state across retries.

Quick Start

Initiate Ralph with your task prompt to begin the iterative, ground-truth task execution.

Frequently Asked Questions about ralph

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

FAQPage Schema
How do I automate task persistence and prevent silent failures in long-running AI workflows?

Automated task persistence prevents silent failures by orchestrating a continuous loop that retries incomplete work and requires architect verification before marking completion. It delegates parallel work to specialized agents while maintaining durable state across failures.

What is the best way to ensure AI task completion is actually verified before delivery?

Ensuring AI task completion requires a strict verification loop that demands fresh verification evidence from an architect before declaring a task complete. This prevents incomplete deliveries by enforcing guardrails and mandatory verification on every iteration.

Can I use parallel agent orchestration for multi-step tasks that need automatic retries?

Parallel agent orchestration supports multi-step tasks by delegating work to specialized agents simultaneously and providing automatic retries on failure. It persists context across sessions to maintain state and ensure durable execution for long-running processes.

Does AI-orchestration work with strict guardrails for complex task execution?

AI-orchestration works with strict guardrails by enforcing mandatory architect verification and requiring fresh evidence before marking any task complete. This ensures auditable outcomes and prevents silent failures during complex, long-running task execution.

How do I start an iterative task execution loop for automated verification?

Starting iterative task execution involves initiating the process with a task prompt to begin the ground-truth execution loop. The system then automatically handles parallel delegation, context persistence, and architect verification until the task is proven complete.