learn

Research topics via Exa deep researcher, web search, or basic search with provenance metadata.

Updated Aug 23, 2026

Search Tags:#automation #workflow #research #provenance #knowledge-graph #learn #topics

Ready to run

npx skills add https://github.com/achousal/EngramR --skill learn-achousal

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: learn
Source: https://github.com/achousal/EngramR/tree/main/.claude/skills/learn
Command: npx skills add https://github.com/achousal/EngramR --skill learn-achousal

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Research and organize topic exploration to grow your knowledge graph using Exa deep researcher, web search, or basic search, while preserving full provenance and pipeline compatibility.

Core Features & Use Cases

Consolidated research workflow across multiple tools (Exa deep researcher, web search, basic search) to discover, verify, and connect claims.
Provenance-rich results: each finding is documented with sources, context, and chain to processing steps.
Automated workflow chaining: outputs feed into subsequent reduce/reflect/evolve steps to expand the graph.

Quick Start

Ask me to learn a topic with /learn or 'research this' and I'll start a guided research session.

Frequently Asked Questions about learn

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

FAQPage Schema

How do I automate a research workflow to build a knowledge graph?▼

Automating a research workflow to build a knowledge graph involves identifying a topic and initiating a structured search cascade. This process assembles provenance-rich results, writes findings to a processing pipeline, and optionally updates goals as new directions are discovered.

What is provenance-rich research data and how does it connect claims?▼

Provenance-rich research data documents each finding with its original sources, context, and processing chain. This ensures claims are verifiable and traceable, allowing subsequent reduce, reflect, and evolve steps to reliably expand the knowledge graph.

How do I use Exa deep researcher and web search for topic exploration?▼

Using Exa deep researcher and web search for topic exploration requires initiating a guided research session. The workflow applies a configured tool cascade to gather evidence, determines research depth, and produces a results document in the inbox with full provenance metadata.

Can I chain research outputs into subsequent workflow steps automatically?▼

Yes, research outputs feed into subsequent reduce, reflect, and evolve steps automatically. This automated workflow chaining expands the knowledge graph by connecting verified claims and writing findings directly to the processing pipeline.

Does the research workflow support updating goals when new directions are discovered?▼

Yes, the research workflow optionally updates goals as new directions are discovered during the evidence gathering process. This ensures the knowledge graph evolves dynamically while maintaining full provenance and pipeline compatibility.