modernisation-decompose

Decompose Java reverse-engineering reports into candidate feature boundaries.

1|Updated Mar 12, 2026
One-click install
npx skills add https://github.com/heymishy/skills-repo --skill modernisation-decompose
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: modernisation-decompose
Source: https://github.com/heymishy/skills-repo/tree/main/.github/skills/modernisation-decompose
Command: npx skills add https://github.com/heymishy/skills-repo --skill modernisation-decompose

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Bridges reverse-engineering outputs with discovery inputs by automatically deriving candidate feature boundaries from Java-based architectures and generating a ready-to-use features document for planning discovery.

Core Features & Use Cases

  • Detects candidate feature boundaries from Maven modules, Spring services, JPA aggregate roots, and transactional spans.
  • Outputs artefacts/[system-slug]/candidate-features.md for direct use in /discovery without manual augmentation.
  • Enables end-to-end workflow from /reverse-engineer outputs to a structured feature set for governance and planning.

Quick Start

Invoke /modernisation-decompose after generating a reverse-engineering report to produce discovery-ready features for your target system.

Frequently Asked Questions about modernisation-decompose

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

FAQPage Schema
How do I identify feature boundaries from a reverse-engineering report?

You can derive candidate feature boundaries by analyzing Java architectural signals such as Maven modules, Spring services, and JPA aggregates directly from your reverse-engineering report.

How do I extract Spring services and Maven modules for enterprise modernisation discovery?

Extract Spring services and Maven modules by decomposing reverse-engineering outputs to detect transactional spans and JPA aggregate roots, producing a structured candidate-features.md document for discovery.

Can I generate discovery-ready features directly from Java reverse-engineering outputs?

Yes, you can generate discovery-ready features directly from Java reverse-engineering outputs. The process bridges reports to discovery by producing a candidate-features.md file that requires no manual augmentation.

What signals are needed to detect candidate feature boundaries in a Java monolith?

Detecting candidate feature boundaries in a Java monolith requires reverse-engineering signals from Maven modules, Spring services, JPA aggregate roots, and transactional spans to accurately map the architecture.

Does this decomposition approach work without a prior reverse-engineering report?

No, this decomposition approach requires an existing reverse-engineering report. It specifically processes the reverse-engineering-report.md artefact to produce candidate features and corpus state outputs.