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ingest

Ingest unstructured content into a knowledge brain with citations and linked entities.

Updated Jun 20, 2026
Search Tags:#document processing#knowledge graph#ingestion#meeting analysis#entity extraction#source citation
One-click install
npx skills add https://github.com/Sigmacodeat/subsumio-web --skill ingest-sigmacodeat
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ingest
Source: https://github.com/Sigmacodeat/subsumio-web/tree/main/server/skills/ingest
Command: npx skills add https://github.com/Sigmacodeat/subsumio-web --skill ingest-sigmacodeat

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill solves the challenge of capturing, organizing, and preserving knowledge from conversations, documents, meetings, media, and web content while maintaining provenance and connections between entities.

Core Features & Use Cases

  • Content Routing: Detects incoming content types and delegates ingestion to specialized workflows for meetings, articles, media, documents, and conversations.
  • Knowledge Graph Enrichment: Extracts entities, updates brain pages, creates relationships, maintains timelines, and preserves source citations.
  • Use Case: Transform a meeting transcript, article URL, or document collection into a structured knowledge base with linked people, companies, concepts, and events.

Quick Start

Use the ingest skill to process this meeting transcript and save the key people, companies, decisions, and sources to the brain.

Frequently Asked Questions about ingest

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

FAQPage Schema
How do I extract entities from meeting transcripts and build a linked knowledge base?▼

Ingesting unstructured content builds a connected knowledge brain by extracting entities, creating relationship backlinks, and preserving source citations for meetings, articles, and documents.

What is the best way to organize unstructured documents with traceable source citations?▼

Organizing unstructured documents with traceable citations requires an ingestion workflow that synchronizes structured pages, extracts entities, and maintains provenance backlinks across all captured content.

How do I process unstructured content into a knowledge graph with linked entities?▼

Processing unstructured content into a knowledge graph requires routing incoming materials to specialized workflows that extract entities, update timelines, and create relationships between people, companies, and concepts.

Can I use document ingestion to automatically update timelines and create relationship backlinks?▼

Yes, document ingestion automatically updates timelines and creates relationship backlinks by detecting content types and delegating processing to workflows that enrich the knowledge graph with structured page synchronization.

Does knowledge graph ingestion work for both meeting transcripts and web articles?▼

Yes, knowledge graph ingestion works for meeting transcripts, web articles, media, and documents by detecting incoming content types and delegating them to specialized workflows for entity extraction and source preservation.

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