enrich

Aggregate external data and internal context into cross-linked intelligence pages.

Updated Jun 2, 2026
One-click install
npx skills add https://github.com/Ninatuzi/gbrain --skill enrich-ninatuzi
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: enrich
Source: https://github.com/Ninatuzi/gbrain/tree/main/skills/enrich
Command: npx skills add https://github.com/Ninatuzi/gbrain --skill enrich-ninatuzi

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill solves the problem of fragmented, forgetful AI memory by transforming raw inputs into a structured, cross-linked intelligence dossier.

Core Features & Use Cases

  • Tiered Enrichment: Automatically scales research depth based on entity importance, from quick social lookups to deep web research.
  • Self-Wiring Knowledge Graph: Automatically creates typed links and backlinks between people, companies, and projects to ensure no information is siloed.
  • Use Case: When you receive a meeting transcript, this skill extracts all mentioned entities, checks your existing brain for context, performs necessary web research, and updates your personal CRM with a structured, cited dossier.

Quick Start

Use the enrich skill to research the company mentioned in the latest meeting transcript and update the brain.

Frequently Asked Questions about enrich

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

FAQPage Schema
How do I build a self-wiring knowledge graph from meeting transcripts?

To build a self-wiring knowledge graph from meeting transcripts, the enrich skill extracts all mentioned entities, cross-references your existing brain context, and creates typed links with bidirectional back-links between people, companies, and projects. This ensures no information is siloed in your personal CRM.

What is tiered enrichment for contact research?

Tiered enrichment for contact research automatically scales the depth of data aggregation based on entity importance. It ranges from quick social lookups for basic contacts to deep web research for key industry figures and collaborators, ensuring research depth matches relevance.

Can I use this knowledge graph skill without a personal CRM database?

No, this knowledge graph skill requires integration with an internal brain database and search tools. It relies on internal database access to check existing context and maintain structured, cross-linked intelligence dossiers with bidirectional back-links.

How do I automate company research and create cross-linked intelligence pages?

You can automate company research by feeding raw inputs like transcripts into the system. It aggregates external data and internal brain context, performs necessary web research, and generates structured, cited intelligence pages that automatically wire typed links to related entities.

What's the best way to maintain an intelligent knowledge graph without fragmented AI memory?

The best way to maintain an intelligent knowledge graph without fragmented AI memory is to transform raw inputs into structured dossiers using automatic typed link and backlink creation. This prevents siloed data by ensuring all people, companies, and projects remain cross-linked.

Are there limitations when enriching person and company entities automatically?

A limitation when enriching person and company entities is that research depth is strictly managed by a tiered protocol. Entities must be categorized as contacts, collaborators, or industry figures to determine whether quick social lookups or deep web research are executed.