- name
- paper-impact-analyzer
- description
- Analyze academic paper impact using multiple data sources (arXiv, GitHub, OpenAlex, Semantic Scholar). Input an arXiv ID and get a multi-dimensional impact assessment with graceful degradation when APIs are unavailable. Use when evaluating paper influence, comparing papers, or assessing whether a paper is worth reading.
- version
- 1.0.0
- allowed-tools
- Bash Read Write
- license
- MIT-0
- metadata
- skill-author
- haataa
- version
- 1.0.0
- openclaw
- emoji
- 📊
- requires
- bins
- ["python"]
Paper Impact Analyzer
Multi-source, fault-tolerant academic paper impact analysis.
When to Use
- Evaluating a paper's academic influence or community adoption
- Comparing impact across multiple papers
- Deciding whether a paper is worth reading based on external signals
- Checking GitHub stars, citation counts, venue acceptance for a paper
- Assessing author credibility (h-index) for a paper
- Batch-analyzing papers in a survey or literature review
How to Use
Single paper
Run the analysis script with an arXiv ID:
python scripts/analyze.py 2603.04948Multiple papers
Pass multiple arXiv IDs separated by spaces:
python scripts/analyze.py 2603.04948 2602.15922 2603.05488 2602.22661Output
The script prints a structured Markdown impact report for each paper, including:
| Dimension | Example |
|---|---|
| Publication date | 2026-03-05 (20 days ago) |
| Venue acceptance | ICLR 2026 |
| GitHub repo | 2,263 stars / 214 forks |
| Citation count | 12 (OpenAlex) / 15 (S2) |
| Author h-index | First author h=23 |
| Affiliations | UC Berkeley, UT Austin |
Plus a synthesized overall rating (S/A/B/C/D) with confidence level and data completeness.
Data Sources (Priority Order)
- arXiv API — paper metadata, authors, abstract (always available)
- GitHub API — repo stars, forks, issues (most reliable external signal)
- OpenAlex API — citation count (free, no API key needed)
- Semantic Scholar API — citations, influential citations, author h-index (rate-limited)
Each source fails independently. The script always produces output using whatever data is available.
Design Philosophy
- Graceful degradation: Every API call is wrapped in try/except with timeouts. If Semantic Scholar returns 429, the report still includes arXiv + GitHub + OpenAlex data.
- Age-aware scoring: Papers < 3 months old are scored primarily on GitHub + venue + team. Papers > 1 year old are scored primarily on citations.
- No API keys required: All data sources used are free and keyless.
- Single file: The entire implementation is in
scripts/analyze.pywith zero external dependencies (stdlib only).