research-wiki

Aggregate papers, ideas, experiments, and claims into a structured knowledge base.

Updated Apr 1, 2026
One-click install
npx skills add https://github.com/Wenwen555/ARIS-LVLM --skill research-wiki
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: research-wiki
Source: https://github.com/Wenwen555/ARIS-LVLM/tree/main/skills/research-wiki
Command: npx skills add https://github.com/Wenwen555/ARIS-LVLM --skill research-wiki

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The persistent knowledge base captures papers, ideas, experiments, and claims across the entire research lifecycle, enabling structured search, traceability, and cross-linking for long-term projects.

Core Features & Use Cases

  • Four entity types: papers, ideas, experiments, and claims with auto-generated relationships.
  • Graph-powered discovery: automatic connections in a central graph to reveal dependencies and lineage.
  • Lifecycle workflows: supports init, ingest, query, update, lint, and stats to manage a research project.
  • Use Case: build a living wiki that grows as you read papers and run experiments, linking results to claims and ideas.

Quick Start

Initialize the wiki with /research-wiki init, then ingest papers with /research-wiki ingest "<title>" — arxiv: <id> and query with /research-wiki query "<topic>".

Frequently Asked Questions about research-wiki

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

FAQPage Schema
How do I organize research papers and link them to my experiments?

A persistent research knowledge base captures papers, ideas, experiments, and claims across the research lifecycle, enabling structured search and cross-linking so you can trace claims back to source literature and experimental results.

How do I build a literature review knowledge base that connects papers to claims?

Initialize the wiki to start a literature review, then ingest papers by title and arXiv ID. The system automatically generates a graph connecting papers, ideas, experiments, and claims, creating a living wiki that grows as you read.

Can I query my research knowledge base to find relationships between ideas and papers?

Yes, you can query the knowledge base by topic to find graph-powered relationships. Automatic connections in the central graph reveal dependencies and lineage between your ingested papers, ideas, experiments, and claims.

What's the best way to maintain experimental traceability for a long-term research project?

Using a persistent wiki with update and lint subcommands maintains experimental traceability by ensuring cross-linked experiments, papers, and claims remain structured and discoverable throughout the entire long-term project lifecycle.

Does this research wiki support structured search across papers, ideas, experiments, and claims?

Yes, the research wiki supports structured search across papers, ideas, experiments, and claims using frontmatter-driven discovery and query subcommands to navigate the interconnected knowledge graph.