research-lit

Find and summarize research papers across local libraries and online academic sources.

Updated May 20, 2026
One-click install
npx skills add https://github.com/lightrain-a/medtrace-aris --skill research-lit-lightrain-a
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: research-lit
Source: https://github.com/lightrain-a/medtrace-aris/tree/main/.vendor/aris/skills/research-lit
Command: npx skills add https://github.com/lightrain-a/medtrace-aris --skill research-lit-lightrain-a

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Research-lit helps you quickly find relevant academic papers and then understand the key ideas, relationships, and consensus in a field without manually hunting through databases and PDFs.

Core Features & Use Cases

  • Multi-source literature discovery: Searches Zotero and an Obsidian vault when available, then scans local PDFs, and finally uses web search/arXiv metadata for broader coverage.
  • Optional advanced discovery & metadata enrichment: Can additionally query Semantic Scholar (for venue/journal metadata), DeepXiv (progressive retrieval), Exa (content-extracted web research), Gemini (AI-driven discovery), and OpenAlex (open citation graph and affiliations) based on explicit source directives.
  • Actionable synthesis output: Produces a structured literature table (paper, venue, method, key results, relevance, source) plus a narrative landscape summary, optionally ingesting results into a research wiki when present.

Quick Start

Use the research-lit skill to find and summarize related work for a topic by running the command: /research-lit "diffusion models for medical imaging" — sources: web,semantic-scholar,local.

Frequently Asked Questions about research-lit

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

FAQPage Schema
How do I find relevant research papers for a literature review across different sources?

You can find relevant research papers for a literature review by searching local Zotero libraries and Obsidian vaults, then expanding to web and arXiv sources. The tool de-duplicates results and extracts bibliographic metadata with summaries to produce a structured table and synthesized narrative.

Can I search my local Zotero library and arXiv at the same time for related work?

Yes, you can search your local Zotero library and arXiv simultaneously for related work. The tool parses a topic argument, honors optional source directives, and de-duplicates results across local and online academic sources into a unified structured literature table.

What is the best way to summarize what specific academic papers claim?

The best way to summarize what specific academic papers claim is to query academic sources like Semantic Scholar and DeepXiv for metadata extraction. This yields a structured table detailing methods, key results, and relevance alongside a synthesized narrative summary.

Does Semantic Scholar integration provide venue and journal metadata for paper discovery?

Yes, Semantic Scholar integration provides venue and journal metadata for paper discovery. By specifying explicit source directives, the tool queries Semantic Scholar to enrich the structured literature table with detailed publication venue and journal information.

How do I generate a structured literature table from local PDFs and online academic sources?

You generate a structured literature table from local PDFs and online academic sources by parsing a topic and scanning connected databases. The tool extracts paper titles, venues, methods, key results, and relevance scores to build the table and a narrative landscape summary.

What are the limitations of using automated paper summarization for a research literature review?

Limitations of automated paper summarization for a literature review include the reliance on explicit source directives for advanced discovery. Without specifying sources like OpenAlex or Exa, queries default to local libraries and basic web searches, potentially missing deeper citation graph data.