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reversa-writer

Generate requirements, design, and tasks specifications from Reversa state and config files.

Updated May 5, 2026

Search Tags:#spec generation #design specification #task planning #reverse engineering #legacy documentation #engineering requirements

Ready to run

npx skills add https://github.com/AlexandrePontesjr/calculadora-Juridica --skill reversa-writer-alexandrepontesjr

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: reversa-writer
Source: https://github.com/AlexandrePontesjr/calculadora-Juridica/tree/main/.agents/skills/reversa-writer
Command: npx skills add https://github.com/AlexandrePontesjr/calculadora-Juridica --skill reversa-writer-alexandrepontesjr

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill turns previously extracted legacy knowledge into precise, traceable, unit-by-unit operational specifications that an AI can reimplement faithfully.

Core Features & Use Cases

Engineering-reverse “writer” role: Converts recovered knowledge into formal specs (requirements, design, tasks) following Reversa’s unit layout.
Deterministic folder structure output: Produces canonical files per unit (and optionally contracts/flows/edge cases/decisions/questions) based on granularity and doc level.
Routed generation with guardrails: Reads Reversa state/config/context artifacts first, stops if specs granularity is not decided, and generates incrementally to preserve quality.

Quick Start

Run the Reversa writer to generate requirements, design, and tasks for one selected unit under the configured output folder, using the granularity rules from config.toml and surface.json.

Frequently Asked Questions about reversa-writer

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

FAQPage Schema

How do I generate formal requirements and design specifications from legacy system knowledge?▼

To generate formal design specifications from legacy knowledge, use a reverse engineering writer that reads extracted context and produces traceable requirements.md, design.md, and tasks.md files in a deterministic folder structure.

What is the best way to document legacy code for AI reimplementation?▼

Documenting legacy code for AI reimplementation involves producing unit-by-unit operational specifications with formal requirements, design details, and tasks, ensuring the output is traceable and faithful to the original system.

Do I need configuration files before generating reverse engineering documentation?▼

Yes, generating reverse engineering documentation requires reading state.json, config.toml or config.user.toml, and surface.json first to determine output granularity and language rules before creating specification files.

Can I control the granularity and output format of generated engineering requirements?▼

Yes, you control the granularity and output format of generated engineering requirements through config.toml or config.user.toml, which routes the creation of canonical files, contracts, and edge case artifacts per unit.

Why does my legacy documentation generation stop before producing any output?▼

Legacy documentation generation stops if specs granularity is not decided in the configuration files, applying guardrails to ensure formal specifications are only produced when output rules are explicitly configured.

What files are produced when creating design specifications for a legacy system unit?▼

Creating design specifications for a legacy system unit produces canonical files including requirements.md, design.md, and tasks.md, with optional artifacts for contracts, flows, edge cases, decisions, and questions based on the configured doc level.