ralphinho-rfc-pipeline

Decomposes large features into RFC-driven work units with DAG orchestration and merge queues.

Updated Mar 18, 2026
One-click install
npx skills add https://github.com/freedom909/real-estate-saas --skill ralphinho-rfc-pipeline-freedom909
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ralphinho-rfc-pipeline
Source: https://github.com/freedom909/real-estate-saas/tree/main/.trae/skills/ralphinho-rfc-pipeline
Command: npx skills add https://github.com/freedom909/real-estate-saas --skill ralphinho-rfc-pipeline-freedom909

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Large features often exceed what a single agent pass can implement reliably, leading to broken integrations and unverifiable changes. This Skill splits oversized work into independently verifiable units with explicit dependencies, quality gates, and rollback plans. ## Core Features & Use Cases - DAG Decomposition: Breaks an RFC into work units with id, depends_on, scope, acceptance_tests, risk_level, and rollback_plan fields. - Tiered Complexity Handling: Classifies units into three tiers from isolated file edits to schema, auth, performance, and security changes. - Merge Queue & Recovery: Enforces dependency checks, rebasing, and integration test re-runs, with stall recovery via scope narrowing and retry. - Use Case: When adding a booking system with schema changes, split it into migration, API, and UI units, validate each against acceptance tests, then merge through the queue with integration verification. ## Quick Start Use the ralphinho-rfc-pipeline skill to decompose this feature RFC into dependency-ordered work units with acceptance tests and a merge plan.

Frequently Asked Questions about ralphinho-rfc-pipeline

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

FAQPage Schema
How do I split a large feature into smaller work units for AI agents?▼

Decompose the feature RFC into units each defining id, depends_on, scope, acceptance_tests, risk_level, and rollback_plan. Order units in a DAG so dependencies complete first, then validate each unit independently before merging.

What is a merge queue in multi-agent development workflows?▼

A merge queue serializes unit integration by blocking merges with unresolved dependency failures, rebasing unit branches on the latest integration branch, and re-running integration tests after each queued merge.

How are work units classified by complexity and risk?▼

Units fall into three tiers: Tier 1 covers isolated file edits with deterministic tests, Tier 2 covers multi-file behavior changes with moderate integration risk, and Tier 3 covers schema, auth, performance, or security changes.

What happens when a work unit stalls during implementation?▼

Stalled units are evicted from the active queue, their findings are snapshotted, and a narrowed unit scope is regenerated. The unit is then retried with updated constraints rather than blocking the pipeline.

When should I use RFC decomposition instead of a single agent pass?▼

Use RFC decomposition when a feature is too large for one agent pass to implement and verify reliably. Single-pass execution suits small isolated changes, while decomposition fits multi-file or cross-cutting features needing staged validation.