learn

Researches topics and grows a provenance-driven knowledge graph via automated AI loops.

1|Updated Feb 21, 2026
One-click install
npx skills add https://github.com/wtyler2505/ProtoPulse --skill learn-wtyler2505
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: learn
Source: https://github.com/wtyler2505/ProtoPulse/tree/main/.agents/skills/learn
Command: npx skills add https://github.com/wtyler2505/ProtoPulse --skill learn-wtyler2505

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates topic research and provenance-rich knowledge graph enrichment, saving time and organizing findings for iterative learning and smarter decisions.

Core Features & Use Cases

  • Research topics with configurable depth using Exa deep researcher, web search, or basic search.
  • Automatically record provenance and chain results to downstream processing modules to grow your knowledge graph.
  • Update goals and propose new directions based on findings for ongoing learning workflows.

Quick Start

Invoke the skill by issuing /learn followed by your topic to start a targeted research workflow.

Frequently Asked Questions about learn

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

FAQPage Schema
How do I automate research workflows and build a knowledge graph with AI?

To automate research, invoke the skill with your topic to start a targeted research workflow, using Exa deep researcher, web search, or basic search to gather findings and write results to an inbox with provenance metadata.

Can I configure the research depth for my knowledge graph enrichment?

Yes, you can configure optional deep or shallower research depth when providing explicit topic input, allowing you to control the scope of your AI-driven research loop and knowledge graph enrichment.

Does this research workflow support provenance tracking for knowledge graphs?

Yes, provenance tracking is supported; the research loop automatically records provenance metadata for your knowledge graph and chains results to downstream processing modules for ongoing learning workflows.

What is the best way to use Exa deep researcher for automated topic research?

The best way to use Exa deep researcher is through an automated AI research loop that processes explicit topic input, records provenance, and writes organized findings to an inbox for downstream knowledge graph processing.

Are there prerequisites to run an AI-driven research loop for knowledge graph enrichment?

To run this AI-driven research loop, you need configured tools like Exa deep researcher, web search, and web search fallback enabled in your environment to gather data and write provenance metadata to your inbox.