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.