ralplan

Name: ralplan
Availability: InStock
Author: cheafi

Convert ambiguous task requests into explicit consensus plans via Planner/Architect/Critic refinement.

Updated Feb 23, 2026

Search Tags:#test strategy #agent collaboration #consensus planning #ADR generation #architecture trade-offs #risk pre-mortem #execution gating

Ready to run

npx skills add https://github.com/cheafi/Trading-bot-CC --skill ralplan-cheafi

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ralplan
Source: https://github.com/cheafi/Trading-bot-CC/tree/main/.github/skills/ralplan
Command: npx skills add https://github.com/cheafi/Trading-bot-CC --skill ralplan-cheafi

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It prevents unclear or under-scoped work by turning vague requests into an explicit, testable consensus plan through an iterative Planner/Architect/Critic loop.

Core Features & Use Cases

Consensus planning loop: Generate an initial plan, then refine it through architectural review and critique until approval is reached.
Explicit decision framing: Produce a final plan including ADR (Decision, Drivers, Alternatives, Why chosen, Consequences) to ensure alignment.
Safety via gating: Redirect vague execution requests into a scoping and validation workflow with explicit acceptance criteria.
Deliberate mode for high-risk work: Add pre-mortem risk scenarios and expanded test planning when --deliberate is used.

Quick Start

Run: ralplan a feature rollout plan for the trading bot, including acceptance criteria, test strategy, and the final ADR.

Frequently Asked Questions about ralplan

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

FAQPage Schema

How do I turn an ambiguous feature request into a testable consensus plan?▼

To build a consensus plan from ambiguous requests, this Skill uses an iterative Planner, Architect, and Critic loop to refine scope and generate explicit acceptance criteria. It ensures alignment by producing a final ADR covering decisions, drivers, alternatives, and consequences.

What is the best way to document architecture trade-offs during product planning?▼

Documenting architecture trade-offs is handled through automatic ADR generation, capturing the decision, drivers, alternatives, why it was chosen, and consequences. This explicit decision framing ensures stakeholders understand the rationale behind architectural choices before execution.

Can I use this for high-risk software projects requiring risk pre-mortems?▼

Yes, high-risk software projects can use the deliberate mode to add risk pre-mortem scenarios and expanded test planning. This injects additional safety analysis into the consensus loop, ensuring potential failure modes are evaluated before final user approval.

How does the iterative critique loop work for refining a project rollout strategy?▼

The iterative critique loop works by generating an initial project rollout strategy, then applying architectural review and critique across up to five iterations. The plan is repeatedly refined against quality gates until a testable consensus is reached for final user approval.

Does this approach support execution gating to prevent under-scoped work?▼

Yes, execution gating is a core feature that redirects vague execution requests into a structured scoping and validation workflow. This prevents under-scoped work by enforcing explicit acceptance criteria and requiring final user approval before any execution begins.

When do I need a multi-agent consensus loop for software and product planning?▼

A multi-agent consensus loop is needed for software and product planning when requests are vague and involve complex architectural trade-offs. It ensures quality gates and approval workflows are met through Planner, Architect, and Critic interactions before execution.