ingest

Route and parse meetings, media, and documents into a structured knowledge base.

45|11|Updated Mar 17, 2026
One-click install
npx skills add https://github.com/beyonai/ByClaw --skill ingest-beyonai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ingest
Source: https://github.com/beyonai/ByClaw/tree/main/middleware/openclaw/skills/gbrain/references/ingest
Command: npx skills add https://github.com/beyonai/ByClaw --skill ingest-beyonai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill solves the problem of fragmented information by automatically routing, parsing, and linking meetings, documents, and media into a structured, searchable knowledge base.

Core Features & Use Cases

  • Automated Entity Detection: Automatically identifies people, companies, and concepts in every message and creates back-links to maintain a connected knowledge graph.
  • Multi-Format Ingestion: Processes articles, videos, podcasts, and meeting transcripts, ensuring raw sources are preserved for provenance.
  • Use Case: When you share a meeting transcript or a research article, the skill automatically extracts key insights, updates relevant entity pages, and logs events to a timeline, ensuring your brain stays current without manual filing.

Quick Start

Use the ingest skill to process the provided meeting transcript and update all mentioned entities in the brain.

Frequently Asked Questions about ingest

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

FAQPage Schema
How do I automate knowledge management for meeting transcripts and research articles?

Automate knowledge management by routing and parsing diverse content types like meeting transcripts and articles into a structured knowledge base. This skill automatically extracts key insights, updates relevant entity pages, and logs events to a timeline without manual filing.

What is automated entity extraction and how does it maintain a knowledge graph?

Automated entity extraction identifies people, companies, and concepts in your ingested content and creates back-links to maintain a connected knowledge graph. It ensures your information stays cohesive by cross-referencing extracted data across all processed documents and media.

Can I ingest podcasts and videos alongside text documents into a single knowledge base?

Yes, you can ingest podcasts and videos alongside articles and meeting transcripts. The skill processes multi-format media to ensure raw sources are preserved for provenance while extracting structured insights into your unified knowledge base.

Do I need gbrain storage integration to log timeline events and ensure data provenance?

Yes, gbrain storage integration is required to ensure data provenance and cross-referencing. The skill relies on these entity detection protocols to route parsed content, update entity pages, and accurately log timeline events within your knowledge graph.

What's the best way to organize fragmented information from meetings, media, and documents?

The best way to organize fragmented information is to automatically route, parse, and link meetings, documents, and media into a searchable knowledge base. This approach extracts key insights and maintains back-links to keep your brain current without manual organization.