ralphinho-rfc-pipeline

Orchestrate RFC-driven DAG workflows that decompose features into verifiable work units.

1|Updated Mar 3, 2026
One-click install
npx skills add https://github.com/samymity/bridge-ventures-backend --skill ralphinho-rfc-pipeline-samymity
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ralphinho-rfc-pipeline
Source: https://github.com/samymity/bridge-ventures-backend/tree/main/.claude/skills/ralphinho-rfc-pipeline
Command: npx skills add https://github.com/samymity/bridge-ventures-backend --skill ralphinho-rfc-pipeline-samymity

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps teams break large, multi-part features into independently verifiable work units so integration doesn’t become a high-risk single merge.

Core Features & Use Cases

  • RFC-driven decomposition: Translates an RFC into a DAG-style plan with explicit unit dependencies and scopes.
  • Quality gates per unit: Runs a consistent sequence (research → plan → implement → tests → review → merge-ready report) to produce unit scorecards.
  • Safer integration via merge queues: Enforces dependency checks, rebases to the latest integration branch, and re-runs integration tests after each queued merge.

Use case: When a feature requires multiple risky changes (e.g., schema updates plus behavioral refactors), apply the pipeline to ensure each unit has acceptance tests, rollback plans, and a clear dependency graph before any integration proceeds.

Quick Start

Apply the ralphinho-rfc-pipeline skill to your RFC to generate a unitized DAG plan with acceptance tests, risk levels, rollback plans, and merge-queue-ready integration steps.

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 RFC into independently verifiable work units?▼

RFC-driven decomposition translates large features into a DAG-style plan with explicit unit dependencies and scopes. This ensures integration does not become a high-risk single merge by isolating schema updates and behavioral refactors.

How do merge queues handle dependency failure during multi-part feature integration?▼

Merge queue integration handles dependency failure by enforcing dependency checks before queuing. It rebases units to the latest integration branch and re-runs integration tests after each queued merge to prevent broken upstream states.

Can I enforce acceptance tests and rollback plans for individual feature units?▼

Quality gates enforce per-unit acceptance tests and rollback plans during feature development. Each work unit undergoes research, planning, implementation, testing, and review to produce a unit scorecard before merge integration.

What is the best way to manage dependency-aware DAG orchestration for complex feature development?▼

DAG orchestration manages complex feature development by decomposing RFCs into a dependency graph of work units. It sequences research, implementation, and validation tasks to ensure safer integration of risky multi-part changes.

Does RFC pipeline orchestration work for features requiring both schema updates and behavioral refactors?▼

RFC pipeline orchestration works for features requiring both schema updates and behavioral refactors. It unitizes these risky changes into a dependency-aware plan, applying acceptance tests and controlled merge-queue integration to each unit.

Why does a merge queue require rebasing and re-testing after each unit integration?▼

Merge queues require rebasing and re-testing after each unit integration to validate dependencies against the updated branch. This controlled integration step ensures that newly merged code does not break existing functionality or upstream dependencies.