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.