What problem does it solve?
This Skill consolidates dispersed signals about an academic paper — venue, citations, code availability and health, reproducibility evidence, social discussion, and author reputation — into a single scored markdown report to help researchers decide what to read, cite, or build on.
Core Features & Use Cases
- Metadata aggregation — fetch title, authors, date, abstract, venue, and citation counts via arXiv and Semantic Scholar.
- Code discovery and health checks — locate official or linked GitHub repositories via Papers With Code and web search and report stars, forks, last push, and issues.
- Reproducibility & adoption signals — detect HuggingFace models/datasets, third-party reimplementations, and runnable code status.
- Social and impact analysis — search Twitter/X, Reddit, and Hacker News for discussion and measure engagement to inform social buzz scores.
- Use Cases — single-paper deep evaluations, multi-paper topic surveys with ranked scorecards, and triage for reading/citation priorities.
Quick Start
Evaluate the paper given its arXiv URL or DOI and produce a dated, scored markdown evaluation that includes venue, citation metrics, code links and health, reproducibility findings, social discussion, and an overall tier.
