ingest

Route inbound content into brain ingestion workflows with entity extraction and provenance citations.

Updated Apr 23, 2026
One-click install
npx skills add https://github.com/ngochuy13/intern-dev --skill ingest-ngochuy13
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ingest
Source: https://github.com/ngochuy13/intern-dev/tree/main/skills/ingest
Command: npx skills add https://github.com/ngochuy13/intern-dev --skill ingest-ngochuy13

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It converts messy inbound content (meetings, articles, media, documents, and conversations) into structured, cross-referenced brain pages with provenance citations.

Core Features & Use Cases

  • Entity-first ingestion & enrichment: Detects people, companies, concepts, dates, and events on every inbound message and updates or creates brain pages accordingly.
  • Timeline and cross-link propagation: Adds reverse-chronological timeline entries and maintains “Iron Law” back-links between entity pages and the ingested page.
  • Provenance-preserving raw capture: Preserves raw sources/transcripts for every ingested item via gbrain raw uploads and requires transcript back-links for media.
  • Content-type specific workflows: Fetches and summarizes web content, extracts text from PDFs/documents (including OCR when needed), and parses video/podcast transcripts with quotes and speaker attribution.

Quick Start

Use the ingest skill to ingest an item by saying: ingest this meeting/article/transcript, and route it into the brain with full provenance and entity cross-references.

Frequently Asked Questions about ingest

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

FAQPage Schema
How do I extract entities and events from meeting transcripts and documents?

To extract entities and events from meeting transcripts and documents, route the inbound content into an ingestion workflow that detects people, companies, concepts, and dates, then persists the updates into structured brain pages.

What is the best way to organize ingested articles and PDFs with timeline entries?

Organizing ingested articles and PDFs with timeline entries requires adding reverse-chronological timeline entries and maintaining Iron Law back-links between the extracted entity pages and the originally ingested content page.

Can I ingest video and podcast transcripts with speaker attribution?

Yes, you can ingest video and podcast transcripts. The ingestion process parses media transcripts with quotes and speaker attribution, while requiring transcript back-links and preserving the raw source via gbrain uploads.

Does entity extraction work on PDFs and screenshots that need OCR?

Entity extraction works on PDFs and screenshots by extracting text from documents and images, including applying OCR when needed, to route the extracted content into specialized brain ingestion workflows.

How do I preserve raw source provenance when ingesting web pages and social posts?

To preserve raw source provenance when ingesting web pages and social posts, the ingestion process enforces mandatory provenance citations and preserves raw sources and transcripts for every ingested item via gbrain raw uploads.

What are the limitations of cross-referencing ingested content across iterative conversations?

A limitation of cross-referencing ingested content is that the workflow strictly enforces mandatory provenance citations and Iron Law back-links, meaning ingested items without raw source preservation via gbrain cannot be properly routed or persisted.