ralphinho-rfc-pipeline

Decompose oversized features into verifiable work units via an RFC-driven pipeline.

Updated Mar 24, 2026

Search Tags:#verification #multi-agent #decomposition #pipeline #RFC #work-units

Ready to run

npx skills add https://github.com/Oruga420/claude-code-skills --skill ralphinho-rfc-pipeline-oruga420

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ralphinho-rfc-pipeline
Source: https://github.com/Oruga420/claude-code-skills/tree/main/ralphinho-rfc-pipeline
Command: npx skills add https://github.com/Oruga420/claude-code-skills --skill ralphinho-rfc-pipeline-oruga420

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Large features often exceed a single agent's scope and require structured decomposition into independently verifiable work units.

Core Features & Use Cases

RFC intake and DAG decomposition to break features into manageable units.
Unit assignment, implementation, validation, and merge queue orchestration for safe integration.
Recovery and rollback support to handle stalled work units and re-planning.

Quick Start

Define an RFC-driven decomposition for a large feature by creating verifiable work units and triggering the quality pipeline.

Frequently Asked Questions about ralphinho-rfc-pipeline

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

FAQPage Schema

How do I decompose large features into verifiable work units for multi-agent pipelines?▼

Decomposing large features into verifiable work units requires an RFC-driven pipeline that breaks down tasks using DAG decomposition. This ensures each unit is assigned, implemented, and validated independently for traceable delivery across multiple agents.

What is RFC-driven decomposition and when do I need it for feature development?▼

RFC-driven decomposition is a structured process that breaks oversized features into manageable, independently testable units. You need it when large system integration changes exceed a single agent's scope and require traceable, staged validation.

How do I orchestrate work unit assignment and validation across multiple agents?▼

Orchestrating work unit assignment across multiple agents involves routing decomposed tasks through a validation pipeline. The system enforces unit assignment, verification, and merge queue rules to ensure safe integration and testable delivery.

Can I recover and re-plan stalled work units during a DAG decomposition pipeline?▼

Recovering stalled work units during a DAG decomposition pipeline is supported through built-in rollback mechanisms. This allows the system to handle stalled tasks and re-plan the remaining work units without losing traceable progress.

Does this pipeline work for system integration tasks that require staged validation?▼

This pipeline applies directly to system integration tasks requiring staged validation. It enforces RFC intake, unit assignment, and merge queue rules to ensure that large integration changes are split and verified safely across stages.