research-wiki

Ingests papers and records typed relationships in a graph-based research wiki.

Updated May 29, 2026

Search Tags:#knowledge graph #claims #arxiv #experiments #paper ingestion #query pack #research wiki

Ready to run

npx skills add https://github.com/Mang30/myskills --skill research-wiki-mang30

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: research-wiki
Source: https://github.com/Mang30/myskills/tree/main/skills/research-wiki
Command: npx skills add https://github.com/Mang30/myskills --skill research-wiki-mang30

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It turns scattered papers, experiments, and claims into a persistent research wiki that keeps accumulating knowledge and relationships over time.

Core Features & Use Cases

End-to-end knowledge accumulation: Initialize a structured wiki, ingest papers, and maintain an audit trail of changes.
Graph-based relationships: Store typed relationships in a single edges file and use it to auto-generate connections and support future reasoning.
Query-ready summaries: Generate a compressed query pack for fast, context-window-friendly retrieval that includes top gaps and failed ideas.

Quick Start

Ask the AI to initialize the wiki for your project by running: research-wiki init.

Frequently Asked Questions about research-wiki

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

FAQPage Schema

How do I build a persistent research knowledge base from scattered papers and claims?▼

You build a persistent research knowledge base by initializing a structured wiki and ingesting papers to record ideas, experiments, and claims with their typed relationships stored in a graph format.

What is a graph-structured research wiki and how does it organize academic knowledge?▼

A graph-structured research wiki organizes academic knowledge by storing typed relationships between ideas, experiments, and claims in a single edges file, maintaining the graph as the source of truth for auto-generating connections and future reasoning.

Can I ingest arXiv papers into my research wiki automatically?▼

Yes, you can ingest arXiv papers automatically into your research wiki using the single paper ingestion and syncing backfill features, which extract and record claims alongside their typed relationships into the graph.

How do I generate a query pack for fast context-window-friendly retrieval from my research notes?▼

You generate a query pack by compressing your research wiki into a context-window-friendly summary that includes top gaps and failed ideas, enabling fast discovery and retrieval from your accumulated knowledge graph.

Does the research wiki require a specific helper script resolution chain to operate?▼

Yes, the research wiki requires using the canonical helper script resolution chain and delegates wiki operations to the designated research_wiki.py script while maintaining the graph/edges.jsonl file as the source of truth.

What is the best way to maintain the health of a knowledge graph tracking paper experiments and claims?▼

The best way to maintain knowledge graph health is to use the built-in linting feature to audit the edges file, update entity fields, and run sync backfills to ensure all ingested papers and typed relationships remain consistent.