reversa

Orchestrate legacy system reverse-engineering into executable AI-ready specifications.

Updated May 5, 2026
One-click install
npx skills add https://github.com/AlexandrePontesjr/calculadora-Juridica --skill reversa-alexandrepontesjr
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: reversa
Source: https://github.com/AlexandrePontesjr/calculadora-Juridica/tree/main/.agents/skills/reversa
Command: npx skills add https://github.com/AlexandrePontesjr/calculadora-Juridica --skill reversa-alexandrepontesjr

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

The Reversa skill turns a legacy system into actionable, executable specifications by orchestrating a multi-step analysis process, preserving progress across sessions.

Core Features & Use Cases

  • Legacy system mapping and plan execution: reads prior state and runs a sequential agent plan starting from the project “Scout” to map modules and integrations.
  • Stateful, checkpointed workflow: uses .reversa/state.json and step references to safely resume between phases without losing progress.
  • Documentation-level and spec-organization control: prompts for doc_level and persists the specs organization layout in .reversa/config.toml before generating deeper artifacts.

Quick Start

Activate the Reversa orchestrator by typing: /reversa.

Frequently Asked Questions about reversa

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

FAQPage Schema
How do I reverse-engineer a legacy system into executable AI specifications?

You orchestrate legacy system reverse-engineering into executable AI-ready specifications by running a multi-phase project analysis workflow that maps modules, applies checkpointing, and generates structured specs for downstream agents.

What is the best way to maintain progress when analyzing a large legacy codebase across sessions?

Maintaining progress when analyzing a legacy codebase across sessions requires checkpointing state in a dedicated JSON file, which preserves the sequential plan execution and safely resumes the workflow without losing prior module mapping data.

Can I control the documentation level and spec organization layout during reverse-engineering?

Yes, you can control the documentation level and spec organization layout by prompting for user approvals before generating deeper artifacts, then persisting the chosen configuration in a TOML file within the project state directory.

How does checkpointing work in an AI workflow for legacy system mapping?

Checkpointing in an AI workflow for legacy system mapping works by reading and updating a central state JSON file, enforcing sequential plan execution, and gating progress on user approvals to ensure documentation phases complete safely.

Where are generated specifications and reverse-engineering artifacts written during the workflow?

Generated specifications and reverse-engineering artifacts are written exclusively to allowed directories, including the state directory, the SDD output folder, and limited forward history paths to prevent unauthorized file modifications.