deepxiv-trending-digest

To summarize trending arXiv papers into a markdown research digest, this Skill orchestrates trending fetches, extracts key metadata and TLDRs, inspects paper sections, and generates a ready-to-share markdown report for weekly roundups.

The best way to automate a weekly lab roundup of DeepXiv papers is to run the digest workflow, which pulls trending papers for a specified window, ranks top candidates for deeper inspection, and outputs a concise markdown digest for literature review.

Yes, you can select specific sections like Introduction, Methods, or Results when summarizing research papers, as the workflow inspects paper structure and extracts targeted sections to inform the final markdown digest generation.

Yes, the workflow extracts paper metadata including title, authors, date, arXiv ID, and TLDR for fast screening, ranking candidates to suggest top papers for optional deeper inspection during the research digest creation.

To generate a markdown digest from a custom window of trending research papers, the Skill fetches DeepXiv trending content for periods like the last 7 or 14 days, briefs candidates, and compiles the findings into a clean markdown file.

An automated digest for literature reviews relies on trending fetches and section extractions rather than full-text comprehension, meaning it provides concise summaries and candidate ranking for brief reading instead of replacing comprehensive manual analysis.