learn

Automate topic research with provenance-rich outputs for knowledge graph workflows.

Updated Feb 3, 2026
One-click install
npx skills add https://github.com/LopeWale/amplLABS --skill learn-lopewale
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: learn
Source: https://github.com/LopeWale/amplLABS/tree/main/.claude/skill-sources/learn
Command: npx skills add https://github.com/LopeWale/amplLABS --skill learn-lopewale

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Researching topics and building a connected knowledge graph can be time-consuming and hard to track with provenance. This skill automates topic exploration using Exa deep researcher, web search, and basic search, yielding results with full provenance and guiding the workflow into a processing pipeline.

Core Features & Use Cases

  • Automated topic exploration using configurable research tools and depth.
  • Provenance-rich outputs with links to sources and a structured inbox workflow.
  • Chains results into downstream processing steps for knowledge graph updates and goals planning.
  • Use Case: Academic literature review, competitive topic analysis, or building a topic knowledge graph for a project.

Quick Start

Provide a topic or command like '/learn machine learning' to start the 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 topic research to build a provenance-rich knowledge graph?

Automating topic research to build a provenance-rich knowledge graph requires configurable research tools like Exa deep researcher or web search, which yield structured outputs with source links channeled into a processing pipeline.

What is the best way to conduct academic literature review with structured provenance?

The best way to conduct academic literature review with structured provenance is automating topic exploration with deep research tools, generating outputs with full source links that feed into a structured inbox workflow.

Can I chain research results into downstream processing for knowledge graph updates?

You can chain research results into downstream processing for knowledge graph updates by directing automated topic exploration outputs into a defined processing pipeline for goals planning.

Do I need configurable research tools like Exa deep researcher to automate topic exploration?

Configurable research tools like Exa deep researcher, web search, or basic search are required to automate topic exploration and generate provenance-rich outputs for a structured inbox workflow.

How does automated topic exploration handle competitive product discovery workflows?

Automated topic exploration handles competitive product discovery workflows by applying configurable search depth and chained processing steps to structure findings into a provenance-rich knowledge graph.

What are the limitations of automating knowledge graph growth through topic research?

Limitations of automating knowledge graph growth through topic research include the dependency on predefined configurable research tools and a defined inbox processing pipeline to structure outputs with full provenance.