ralphinho-rfc-pipeline

This skill uses RFC-driven decomposition to break large features into smaller, independently verifiable work units for multi-agent orchestration. It manages work unit decomposition by specifying dependencies, scope, acceptance tests, risk levels, and rollback plans for each component.

A multi-agent DAG execution pattern orchestrates complex feature development by structuring tasks as a directed acyclic graph. This approach coordinates multiple agents through defined pipeline stages, quality gates, and merge queues to validate interdependent components before integration.

Manage quality gates and merge queues by orchestrating a pipeline with defined stages and quality checks. This validates each decomposed work unit independently before integration, preventing faulty components from entering the main branch during complex feature development.

Yes, you can use RFCs to decompose a new microservice with multiple interdependent components. The pipeline manages the RFC process to break down the work and validates each component against quality gates before integration.

The best way to specify dependencies and rollback plans is through detailed unit specifications within an RFC pipeline. This ensures every decomposed work unit includes scope, acceptance tests, risk levels, and rollback plans for safe integration.

You need an RFC pipeline for agent orchestration when developing large, complex features that are too big for a single agent pass. It breaks the work into independently verifiable units to manage dependencies and validate components before integration.