ralphinho-rfc-pipeline

Execute multi-agent feature workflows with quality gates and merge queues.

Updated Nov 19, 2025
One-click install
npx skills add https://github.com/Sake-Team/SmartSake --skill ralphinho-rfc-pipeline-sake-team
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ralphinho-rfc-pipeline
Source: https://github.com/Sake-Team/SmartSake/tree/main/backup/skills/ralphinho-rfc-pipeline
Command: npx skills add https://github.com/Sake-Team/SmartSake --skill ralphinho-rfc-pipeline-sake-team

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps in managing large-scale features by breaking them into independently verifiable work units and ensuring quality through the RFC-driven execution process.

Core Features & Use Cases

  • RFC-Driven Workflow: Orchestrates feature decomposition into independently verifiable work units.
  • Multi-Agent DAG Execution: Facilitates execution patterns with quality gates, merge queues, and work unit orchestration.
  • Use Case: For a feature too large for a single agent, this skill breaks it into work units that are verified at each stage, ensuring a quality-first development approach.

Quick Start

Load the ralphinho-rfc-pipeline skill to execute the RFC for a new feature 'FeatureX'.

Frequently Asked Questions about ralphinho-rfc-pipeline

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

FAQPage Schema
How do I break down a large software feature into independently verifiable work units?

RFC-driven workflow decomposes large features into verifiable work units by orchestrating execution through defined stages. This ensures a quality-first development approach for features too large for a single agent to handle.

How does multi-agent DAG execution handle quality assurance for complex feature development?

Multi-agent DAG execution facilitates complex feature workflows by applying quality assurance gates and merge queues at each stage. This verifies work units independently before progressing through the directed acyclic graph pattern.

What is an RFC-driven workflow and when do I need it for large-scale software projects?

An RFC-driven workflow is an execution process that manages large-scale features by breaking them into independently verifiable work units. You need it when a feature is too large for a single agent and requires strict quality gates.

Do I need a multi-agent system already in place to use DAG execution with quality gates?

Yes, DAG execution with quality gates requires a multi-agent system with a defined DAG and quality gates already in place. The skill orchestrates work units within this existing infrastructure rather than creating the agents.

What's the best way to orchestrate work units across multiple agents for feature decomposition?

Work unit orchestration is best handled through RFC-driven execution that breaks features into verifiable units and processes them via DAG patterns. This approach ensures each stage passes quality assurance gates before merging.

What are the limitations of using DAG execution patterns for feature decomposition?

DAG execution for feature decomposition requires a predefined multi-agent system and established quality gates to function. Without these infrastructure prerequisites in place, the work unit orchestration cannot verify stages independently.