Knowledge

Name: Knowledge
Availability: InStock
Author: starlink-awaken

Organize and query the PAI Knowledge Archive across four entity domains.

1|Updated Jun 10, 2026

Search Tags:#search #memory #ingestion #knowledge #archive #graph #wikilinks

Ready to run

npx skills add https://github.com/starlink-awaken/pai-universal --skill knowledge-starlink-awaken

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Knowledge
Source: https://github.com/starlink-awaken/pai-universal/tree/main/templates/packs/Knowledge/src
Command: npx skills add https://github.com/starlink-awaken/pai-universal --skill knowledge-starlink-awaken

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Knowledge skill consolidates and structures notes into a typed, interlinked archive, enabling reliable search, provenance, and growth of domain knowledge across People, Companies, Ideas, and Research.

Core Features & Use Cases

Supports a formalized schema for frontmatter-driven notes and 8 relationship types (supports, contradicts, extends, part-of, instance-of, caused-by, preceded-by, related)
Enables deterministic operations: search (lexical, frontmatter, wikilink), add with typed links, harvest, develop, ingest, and graph analytics
Provides ripples across related notes when ingesting sources, maintaining consistency and traceability

Quick Start

Start by assessing the archive and running a harvest, then perform a basic search to locate related notes.

Frequently Asked Questions about Knowledge

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

FAQPage Schema

How do I organize a connected knowledge archive with typed relationships between notes?▼

Knowledge ingestion uses ripple effects to update related notes automatically, maintaining consistency and traceability across the archive. When ingesting sources, the system applies frontmatter schemas and propagates changes through wikilinks to keep interconnected notes synchronized.

What is ripple ingestion and how does it maintain consistency across linked notes?▼

Ripple ingestion maintains consistency by propagating changes across related notes when new sources are added. It applies frontmatter schemas and typed relationships during writes, ensuring traceability and automatic updates throughout the interconnected knowledge graph.

Can I search a knowledge archive using frontmatter fields and wikilinks?▼

Yes, the archive supports a 3-pass search covering lexical content, frontmatter fields, and wikilinks. This deterministic approach locates notes across People, Companies, Ideas, and Research domains without requiring external dependencies.

What is the best way to manage notes across multiple entity domains in a knowledge graph?▼

The best way to manage notes across entity domains is to apply structured linking and MOC regeneration during writes. This maintains a typed, interlinked archive across People, Companies, Ideas, and Research domains with provenance tracking and graph analytics.

Does this knowledge archive approach require external dependencies to run graph analytics?▼

No dependencies are required. The archive performs graph analytics, 3-pass search, and ripple ingestion natively by applying frontmatter schemas and typed relationships such as caused-by and preceded-by directly during write operations.

When should I use MOC regeneration and typed relationships in a knowledge archive?▼

Use MOC regeneration and typed relationships during write operations to ensure frontmatter schemas are applied and the knowledge graph remains consistent. This maintains traceability and enables reliable harvest and search across the archive.