ralphinho-rfc-pipeline

Name: ralphinho-rfc-pipeline
Availability: InStock
Author: gganbukim

Decompose RFCs into dependency-aware DAG workflows with quality gates and merge-queue safety.

Updated May 4, 2026

Search Tags:#dependency management #multi-agent #quality gates #rfc #merge queue #unit validation #dag orchestration

Ready to run

npx skills add https://github.com/gganbukim1/myskills --skill ralphinho-rfc-pipeline-gganbukim1

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Please help me install this Agent Skill.
Skill: ralphinho-rfc-pipeline
Source: https://github.com/gganbukim1/myskills/tree/main/ralphinho-rfc-pipeline
Command: npx skills add https://github.com/gganbukim1/myskills --skill ralphinho-rfc-pipeline-gganbukim1

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It solves the challenge of breaking large, multi-faceted features into independently verifiable work units while maintaining quality gates, dependency safety, and controlled integration.

Core Features & Use Cases

RFC-driven decomposition and DAG orchestration: Turn a broad proposal into a dependency-aware execution plan that multiple agents can complete in parallel.
Per-unit quality pipeline with acceptance criteria: Produce unit-level research, implementation plans, tests, reviews, and merge-ready reports to prevent fragile merges.
Merge queue and recovery guardrails: Enforce rebase and test reruns for every queued merge, and provide a stall-recovery loop to narrow scope and retry.

Quick Start

Use the ralphinho-rfc-pipeline skill to transform your large RFC into a dependency graph and a sequence of merge-safe, acceptance-tested work units.

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 a large RFC into independently verifiable units for parallel development?▼

To break a large RFC into independently verifiable units, you can operationalize RFC decomposition into a multi-agent DAG execution workflow, creating a dependency-aware plan with per-unit quality gates and acceptance tests for parallel completion.

What is the best way to manage dependencies and merge queues for multi-agent feature development?▼

Managing dependencies and merge queues for multi-agent feature development requires tracking explicit unit dependencies and enforcing merge-queue safety, which includes rebase enforcement, integration test reruns, and controlled integration across teams.

How do I enforce quality gates and acceptance tests for individual RFC work units?▼

Enforcing quality gates for RFC work units involves applying a per-unit quality pipeline that produces unit-level research, implementation plans, tests, reviews, and merge-ready reports to prevent fragile merges.

How do I recover from stalled multi-agent DAG orchestration without losing progress?▼

To recover from stalled multi-agent DAG orchestration, you can utilize a stall-recovery loop that narrows scope and retries failed units, ensuring dependency tracking and controlled integration are maintained.

Does multi-agent DAG orchestration work for large features requiring controlled integration across teams?▼

Multi-agent DAG orchestration works for large features requiring controlled integration across teams by turning broad proposals into dependency-aware execution plans that multiple agents complete in parallel with merge-safe units.

Why do I need explicit dependencies and acceptance tests for RFC merge gating?▼

Explicit dependencies and acceptance tests are needed for RFC merge gating to ensure merge queue safety, allowing controlled integration and preventing fragile merges during large feature development.