ralplan

Coordinate Planner, Architect, and Critic to produce an approved consensus plan.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/HaydernCenterpoint/oh-my-qwen --skill ralplan-hayderncenterpoint
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ralplan
Source: https://github.com/HaydernCenterpoint/oh-my-qwen/tree/main/skills/ralplan
Command: npx skills add https://github.com/HaydernCenterpoint/oh-my-qwen --skill ralplan-hayderncenterpoint

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Converts vague prompts into concrete, reviewable plans by coordinating Planner, Architect, and Critic to reach a validated consensus before execution.

Core Features & Use Cases

  • Orchestrated multi-agent planning: Planner crafts the initial plan, Architect strengthens the design, Critic validates quality, and iteration loops until approval.
  • Pre-context intake and gating: Captures context and ensures a concrete plan with ADRs, drivers, alternatives, and test criteria before proceeding.
  • End-to-end readiness: Produces a ready-to-execute plan with staffing guidance, explicit next steps, and risk mitigations.

Quick Start

Invoke ralplan to perform consensus planning for a given task and return an approved plan.

Frequently Asked Questions about ralplan

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

FAQPage Schema
How does consensus planning work for high-stakes AI workflows?

Consensus planning works by orchestrating a Planner, Architect, and Critic to iterate on high-level objectives until they produce a final, approved plan with explicit context intake, risk assessment, and trade-off analysis.

How do I convert vague prompts into concrete, reviewable AI task plans?

To convert vague prompts into concrete plans, you submit high-level objectives to trigger a gated execution process that captures context, applies risk analysis, and outputs an ADR-backed plan with acceptance criteria and staffing guidance.

What is the best way to perform risk analysis and task scoping before AI execution?

The best way to perform risk analysis and task scoping is by running a multi-agent coordination loop where a Critic validates an Architect's design against the initial plan until a testable, ready-to-execute consensus is reached.

Do I need explicit context intake for consensus planning of complex tasks?

Yes, explicit context intake is required for consensus planning because it gates execution, ensuring the final plan includes architectural decision records, drivers, alternatives, and test criteria before any task proceeds.

Can I use multi-agent coordination to generate ADR-backed plans with acceptance criteria?

Yes, you can use multi-agent coordination to generate ADR-backed plans with acceptance criteria by having the Architect strengthen the Planner's initial design and the Critic validate quality through iteration loops until approval.