Home/AI Agent Orchestration & Collaboration/ralphinho-rfc-pipeline
R

ralphinho-rfc-pipeline

by @affaan-mv
4.4(44)

An RFC-driven multi-agent DAG execution model, ensuring quality assurance and efficient collaboration for AI task workflows.

rfc-processtechnical-documentationsoftware-architecturedesign-documentsversion-controlGitHub
Installation
npx skills add affaan-m/everything-claude-code --skill ralphinho-rfc-pipeline
compare_arrows

Before / After Comparison

1 组
Before

Without a structured framework, managing multi-agent collaborative workflows for large-scale feature development or complex tasks can lead to unclear task decomposition, missing quality gates, frequent merge conflicts, and difficulties in coordinating work units, severely impacting project progress and delivery quality.

After

With the Ralphinho RFC Pipeline skill, an RFC-driven multi-agent DAG execution mode has been implemented, integrating quality gates, merge queues, and work unit orchestration. This significantly improves the execution efficiency, quality control, and collaboration smoothness of complex workflows.

SKILL.md

Ralphinho RFC Pipeline

Inspired by humanplane style RFC decomposition patterns and multi-unit orchestration workflows.

Use this skill when a feature is too large for a single agent pass and must be split into independently verifiable work units.

Pipeline Stages

  1. RFC intake
  2. DAG decomposition
  3. Unit assignment
  4. Unit implementation
  5. Unit validation
  6. Merge queue and integration
  7. Final system verification

Unit Spec Template

Each work unit should include:

  • id
  • depends_on
  • scope
  • acceptance_tests
  • risk_level
  • rollback_plan

Complexity Tiers

  • Tier 1: isolated file edits, deterministic tests
  • Tier 2: multi-file behavior changes, moderate integration risk
  • Tier 3: schema/auth/perf/security changes

Quality Pipeline per Unit

  1. research
  2. implementation plan
  3. implementation
  4. tests
  5. review
  6. merge-ready report

Merge Queue Rules

  • Never merge a unit with unresolved dependency failures.
  • Always rebase unit branches on latest integration branch.
  • Re-run integration tests after each queued merge.

Recovery

If a unit stalls:

  • evict from active queue
  • snapshot findings
  • regenerate narrowed unit scope
  • retry with updated constraints

Outputs

  • RFC execution log
  • unit scorecards
  • dependency graph snapshot
  • integration risk summary

User Reviews (0)

Write a Review

Effect
Usability
Docs
Compatibility

No reviews yet

Statistics

Installs3.7K
Rating4.4 / 5.0
Version
Updated2026年5月22日
Comparisons1

User Rating

4.4(44)
5
27%
4
50%
3
20%
2
2%
1
0%

Rate this Skill

0.0

Compatible Platforms

🔧Claude Code
🔧OpenClaw
🔧OpenCode
🔧Codex
🔧Gemini CLI
🔧GitHub Copilot
🔧Amp
🔧Kimi CLI

Timeline

Created2026年3月16日
Last Updated2026年5月22日