current-legacy

Grow system overview, DFD, and I/O interface maps for legacy code.

Updated Mar 11, 2026
One-click install
npx skills add https://github.com/t-hasuike/CLysis --skill current-legacy
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: current-legacy
Source: https://github.com/t-hasuike/CLysis/tree/main/legacy-analysis/skills/current-legacy
Command: npx skills add https://github.com/t-hasuike/CLysis --skill current-legacy

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Progressively understand legacy code through iterative concrete-to-abstract cycles by growing three essential maps (system overview, data-flow diagram, and the I/O interface) rather than building them in one shot.

Core Features & Use Cases

  • Phase-driven map growth for system overview, DFD, and I/O interface
  • Role-based guidance and governance (Shogun, Karo, Ashigaru, Metsuke)
  • F002-rule alignment to separate leadership from execution and enable audits

Quick Start

Describe your target repository and start Phase 0 to begin growing the three maps.

Frequently Asked Questions about current-legacy

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

FAQPage Schema
How do I analyze legacy code to generate system documentation incrementally?▼

Analyze legacy code incrementally by growing three maps—system overview, data-flow diagram, and I/O interface—through iterative concrete-to-abstract cycles across phased stages, producing audit-ready documentation.

What is the best way to map data flow and I/O interfaces in a legacy codebase?▼

Mapping data flow and I/O interfaces is best handled through iterative cycle-driven growth rather than single-shot creation, progressively refining a DFD and interface map from concrete observations to abstract models.

How do I structure team collaboration for legacy code modernization analysis?▼

Structure legacy code analysis collaboration using defined roles—Shogun, Karo, Ashigaru, Metsuke—and F002 governance rules that separate leadership from execution to enable team coordination and audits.

Can I use iterative map growth for codebases transitioning from maintenance to modernization?▼

Iterative map growth is specifically designed for codebases in transition from maintenance to modernization, enabling teams to incrementally generate and validate documentation during Phase 0 through Phase 3.

What are the limitations of building a system overview and DFD in one shot?▼

Building a system overview and DFD in one shot lacks iterative validation, whereas progressive map growth through concrete-to-abstract cycles ensures documentation is continuously validated and audit-ready.