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paper-finder

Discover and organize ML/AI/CV/NLP papers into structured topic folders with BibTeX exports.

2|Updated Mar 4, 2026
Search Tags:#bibtex#arxiv#literature-review#paper-search#semantic-scholar#research-management
One-click install
npx skills add https://github.com/pengqianhan/open-paper-skills --skill paper-finder-pengqianhan
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: paper-finder
Source: https://github.com/pengqianhan/open-paper-skills/tree/main/.claude/skills/paper-finder
Command: npx skills add https://github.com/pengqianhan/open-paper-skills --skill paper-finder-pengqianhan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Discover and organize ML/AI/CV/NLP papers into a structured, queryable knowledge base.

Core Features & Use Cases

  • Search and collect papers across arXiv, semantic scholar, Google Scholar, and major venues.
  • Memory bank & mind graph: maintain per-topic paper records, summaries, BibTeX, and topic relationships.
  • Use cases: build literature reviews, track related work, export BibTeX, and manage research references.

Quick Start

Ask to search for papers on a topic and add them to a new topic folder with memory and BibTeX.

Frequently Asked Questions about paper-finder

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

FAQPage Schema
How do I find ML papers across arXiv and Semantic Scholar and organize them for a literature review?▼

You can search for ML, AI, CV, and NLP papers across arXiv, Semantic Scholar, and Google Scholar. The Skill organizes results into per-topic folders containing a memory bank, mind graph, summaries, and BibTeX exports for your literature review.

Can I automatically export BibTeX citations for papers discovered during a topic-based search?▼

Yes, automatic BibTeX export is supported for each discovered paper. The Skill generates a references.bib file within the specific topic folder, allowing you to directly import citations into your research management system.

How does a memory bank help manage research references and track related work?▼

The memory bank maintains per-topic paper records and summaries in a memory-bank.md file. It builds a mind graph of topic relationships, allowing you to query structured knowledge and track related work efficiently.

Do I need web access to search for papers and build a structured knowledge base?▼

Yes, web access is required. The Skill uses WebSearch and WebFetch components to query arXiv, Semantic Scholar, and Google Scholar, retrieving paper metadata, abstracts, and PDFs to populate the knowledge base.

What is the best way to structure literature searches for major ML venues and track topic relationships?▼

The best way is using per-topic folders to structure searches across major venues. Each folder maintains its own memory bank, mind graph mapping topic relationships, and BibTeX exports, creating a queryable knowledge base.

Can I collect and save PDFs locally when organizing papers into topic folders?▼

Yes, saving PDFs is supported as an optional feature within per-topic folders. Alongside PDFs, the folder structure automatically maintains your memory bank, mind graph, and BibTeX exports for comprehensive research management.

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