Select the most relevant HuggingFace daily paper and generate a LaTeX summary report.
npx skills add https://github.com/jusjinuk/internbot --skill daily-papers
Please help me install this Agent Skill. Skill: daily-papers Source: https://github.com/jusjinuk/internbot/tree/main/.claude/skills/daily-papers Command: npx skills add https://github.com/jusjinuk/internbot --skill daily-papers
Review today's HuggingFace daily papers, pick the most relevant one, and write a LaTeX summary report with 2-3 follow-up research directions to guide next steps.
Ask the agent to fetch today's HuggingFace daily papers, select the most relevant one, and generate a LaTeX summary report with follow-up research directions.
High-intent search queries and answers about installing and using this skill.
The daily paper review process fetches HuggingFace papers, checks a local JSON log to skip previously reviewed papers, and selects the most relevant new publication to summarize in LaTeX with actionable follow-up research directions.
Yes, the review process consults a local papers-log.json file to track previously reviewed papers and automatically filters them out, ensuring only new daily papers are selected for your LaTeX summary reports.
Generating BibTeX metadata for daily paper reviews is handled automatically by selecting the most relevant HuggingFace paper and outputting a structured LaTeX file that includes the citation metadata alongside the summary and research directions.
The workflow outputs a YYYY-MM-DD-daily-papers.tex file containing the paper summary and embedded BibTeX metadata, which you can directly use or include in your existing LaTeX compilation pipeline.
To find follow-up research directions, this Skill analyzes the selected HuggingFace daily paper and automatically generates 2-3 concrete, actionable research steps, appending them directly to your LaTeX summary report.
A key limitation is that the process selects only one paper per day from the HuggingFace daily papers feed and requires maintaining a local JSON log to manage duplicates, meaning it does not batch review multiple papers simultaneously.
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