text-extractor

Extract structured RF, RB, DC, INT, and OBS from technical documents into Markdown.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/apadern/.github_tailormade --skill text-extractor
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: text-extractor
Source: https://github.com/apadern/.github_tailormade/tree/main/skills/text-extractor
Command: npx skills add https://github.com/apadern/.github_tailormade --skill text-extractor

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pdfplumber, pymupdf, pypdf, python-docx, pillow, pytesseract, opencv-python, camelot-py, tabula-py, pandas, pdf2image, rapidfuzz, and includes scripts (resource) components.

What problem does it solve?

This Skill extracts and structures RF (Requerimientos Funcionales), RB (Reglas de Negocio), DC (Decisiones/Condiciones), INT (Integraciones) y OBS (Observaciones) from technical documents (PDF, DOCX, TXT), enabling consistent, auditable requirements derivation.

Core Features & Use Cases

  • Extract RF, RB, DC, INT and OBS from PDFs, Word documents, and text sources.
  • Genera una especificación en Markdown con secciones RF, RB, DC, INT y OBS, e un dump opcional de Contexto General.
  • Soporta OCR de imágenes, reconocimiento de diagramas y extracción de tablas para convertir en reglas de negocio, facilitando trazabilidad y cumplimiento.

Quick Start

Ejecuta extractor_de_requisitos.py con tus documentos de entrada y guarda la salida en requisitos.md.

Frequently Asked Questions about text-extractor

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

FAQPage Schema
How do I extract functional requirements and business rules from a PDF document?

Extracting structured requirements from technical documents involves parsing PDFs, DOCX, and images to identify functional requirements, business rules, and integrations. This Skill uses multi-source text extraction and OCR to produce a structured Markdown specification with RF, RB, DC, INT, and OBS sections.

Can I use OCR to extract requirements from image-based diagrams and tables?

Yes, you can use OCR to extract requirements from images, diagrams, and tables. This Skill applies pytesseract and OpenCV to perform OCR on image-based sources, translating visual tables and diagrams into structured business rules and Markdown specifications.

What is the best way to convert a DOCX file into a structured requirements specification?

The best way to convert a DOCX file into a structured requirements specification is to use a tool that applies contextual extraction to identify RF, RB, and INT elements. This Skill processes DOCX files using python-docx to generate an auditable Markdown spec with dedicated sections.

Does pdfplumber support table extraction for generating compliance documentation?

Yes, pdfplumber supports table extraction for generating compliance documentation. This Skill uses pdfplumber alongside camelot-py and tabula-py to extract tabular data from PDFs, translating it into structured business rules and decision conditions for Markdown output.

How do I generate a Markdown specification from multiple technical documents?

To generate a Markdown specification from multiple technical documents, process your PDF, DOCX, and TXT files using a multi-source extraction script. This Skill consolidates extracted text, OCR data, and tables into a single Markdown file with structured RF, RB, DC, INT, and OBS sections.