kb-ingest

Name: kb-ingest
Availability: InStock
Author: LuminaVault

Classify and store URLs, PDFs, images, and text notes into a knowledge base.

Updated May 9, 2026

Search Tags:#knowledge base #content ingestion #image processing #PDF handling #text management

Ready to run

npx skills add https://github.com/LuminaVault/LuminaVaultServer --skill kb-ingest-luminavault

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: kb-ingest
Source: https://github.com/LuminaVault/LuminaVaultServer/tree/main/hermes-skills/kb-ingest
Command: npx skills add https://github.com/LuminaVault/LuminaVaultServer --skill kb-ingest-luminavault

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, BeautifulSoup, json, os, re, datetime, tempfile, shutil, jq, python3, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines the process of ingesting various types of content, such as URLs, PDFs, images, and plain text notes, into your personal knowledge base, ensuring efficient organization and accessibility.

Core Features & Use Cases

Content Ingestion: Automatically ingest URLs, PDFs, images, and text notes into the knowledge base's 'raw' directory.
Topic-Based Organization: Content is organized into appropriate subdirectories based on the content's topic, facilitating easy access and management.
Use Case: Quickly add a research article, a PDF document, or a screenshot to your knowledge base for future reference.

Quick Start

To ingest a URL into your knowledge base, run the command: /kb-ingest [URL].

Frequently Asked Questions about kb-ingest

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

FAQPage Schema

How do I automatically ingest URLs and PDFs into a structured knowledge base?▼

To ingest URLs and PDFs into a knowledge base, you can automate content classification and storage by topic into a raw directory. The process extracts text and handles various content types including images and plain text notes.

Does knowledge base content ingestion require Python for image processing and text extraction?▼

Yes, knowledge base content ingestion requires Python for file handling and text extraction. The workflow utilizes Python libraries like BeautifulSoup and jq to process URLs, PDFs, images, and plain text notes.

What is the best way to organize ingested content by topic in a personal knowledge base?▼

Organizing ingested content by topic is best handled by automatically routing URLs, PDFs, and images into appropriate subdirectories within the knowledge base raw directory based on the extracted content subject.

How do I handle API rate limits and security challenges when scraping URLs for a knowledge base?▼

Handling API rate limits and security challenges during URL scraping is managed through built-in fallback mechanisms within the ingestion workflow. These fallbacks ensure content extraction continues smoothly despite access restrictions.

Can I use BeautifulSoup for plain text management when ingesting content into my knowledge base?▼

Yes, you can use BeautifulSoup for plain text management during content ingestion. It works alongside Python dependencies to parse and extract text data from URLs before storing it in your knowledge base structure.