produce-decomposition-ecr

Produces structured ECR decomposition artifacts from analyzed extension intents for operator validation workflows.

1|Updated Apr 20, 2026
One-click install
npx skills add https://github.com/Largo2z9/phantomos --skill produce-decomposition-ecr
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: produce-decomposition-ecr
Source: https://github.com/Largo2z9/phantomos/tree/main/.skills/skills/produce-decomposition-ecr
Command: npx skills add https://github.com/Largo2z9/phantomos --skill produce-decomposition-ecr

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill transforms complex extension intents into a structured operator-facing decomposition, helping teams clarify what should be built before moving into implementation.

Core Features & Use Cases

  • ECR Decomposition Generation: Produces a canonical equation, cartographic matrix, and measurable atoms from an analyzed extension intent.
  • Pattern-Based Template Suggestions: Identifies reusable templates from existing registries and frameworks to accelerate scaffold design.
  • Operator Validation Workflow: Surfaces the decomposition for approval, adjustment, or halt decisions before downstream scaffold phases continue.

Quick Start

Ask the AI to produce an ECR decomposition for the analyzed extension intent and prepare the operator validation artifact.

Frequently Asked Questions about produce-decomposition-ecr

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

FAQPage Schema
How do I create an ECR decomposition map from analyzed extension intents?

To create an ECR decomposition map, you generate a canonical equation, cartographic matrix, and measurable atoms from analyzed extension intents before implementation scaffolding begins.

What is an operator-facing decomposition in extension design workflows?

An operator-facing decomposition is a structured breakdown of extension intents into validated equations and measurable atoms that clarifies what should be built before moving into implementation.

How do I validate decomposition proposals before starting implementation scaffolding?

You validate decomposition proposals by surfacing the generated artifacts for operator approval, adjustment, or halt decisions before any downstream scaffold phases continue.

Can I use existing templates to accelerate ECR decomposition and scaffold design?

Yes, you can use existing templates by identifying reusable patterns from current registries and frameworks to accelerate scaffold design during the decomposition process.

Do I need upstream ECR analysis outputs before generating decomposition artifacts?

Yes, you need access to upstream ECR analysis outputs and registry resources to generate validated decomposition proposals.

What's the best way to structure operator-facing equations and measurable atoms for extension design?

The best way to structure operator-facing equations and measurable atoms is by producing canonical decomposition maps from analyzed intents before implementation scaffolding.