text-extractor

Name: text-extractor
Availability: InStock
Author: apadern

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

Updated Aug 23, 2026

Search Tags:#documents #ocr #markdown #requirements #diagrams #tables #extract

Ready to run

npx skills add https://github.com/apadern/.github_tailormade --skill text-extractor

💬 Prompt for ChatGPT / Claude Chat▼

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.