Arxiv paper lookup

Skill cxcscmu/SkillLearnBench/skills/b1-one-shot-claude-sonnet-4-6/organize-messy-files/arxiv-paper-lookup

[COLM'26] SkillLearnBench is the first benchmark for evaluating continual learning methods that automatically generate agent skills.

Install

npx -y skills add cxcscmu/SkillLearnBench --skill arxiv-paper-lookup

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What its author says it does

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Look up arxiv paper metadata (title, abstract, subject) from arxiv IDs to classify papers by topic without reading full PDFs.

SKILL.md

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Arxiv Paper Lookup Skill

Overview

When files are named with arxiv IDs (e.g., 2305.12773v1.pdf), you can extract metadata via the arxiv API to classify papers by subject without downloading/reading the full PDF.

Extracting Arxiv ID from Filename

import re

def extract_arxiv_id(filename):
    # Strip path and extension
    base = os.path.basename(filename).replace('.pdf', '')
    # Remove version suffix like v1, v2, v3
    arxiv_id = re.sub(r'v\d+$', '', base)
    return arxiv_id  # e.g., "2305.12773"

Fetching Metadata via Arxiv API

import urllib.request
import xml.etree.ElementTree as ET

def fetch_arxiv_metadata(arxiv_id):
    url = f"http://export.arxiv.org/api/query?id_list={arxiv_id}"
    with urllib.request.urlopen(url) as response:
        data = response.read().decode('utf-8')

    root = ET.fromstring(data)
    ns = {'atom': 'http://www.w3.org/2005/Atom'}
    entry = root.find('atom:entry', ns)
    if entry is None:
        return None

    title = entry.find('atom:title', ns).text.strip()
    summary = entry.find('atom:summary', ns).text.strip()
    categories = [c.get('term') for c in entry.findall('{http://arxiv.org/schemas/atom}primary_category', ns)]

    return {'title': title, 'summary': summary, 'categories': categories}

Batch Fetching (up to 100 IDs at once)

def fetch_batch(arxiv_ids):
    id_list = ','.join(arxiv_ids)
    url = f"http://export.arxiv.org/api/query?id_list={id_list}&max_results={len(arxiv_ids)}"
    # ... parse response

Classification Strategy

Use title + abstract keywords to classify
Common arxiv categories: cs.CL, cs.AI (LLM), quant-ph (quantum), gr-qc (black hole), q-bio (DNA/biology)
Titles are usually sufficient for classification

Rate Limiting

Arxiv API allows ~3 requests/second
Add time.sleep(0.5) between batch requests
Batch up to 100 IDs per request