Extract problem, method, findings, and relevance from academic paper text.
npx skills add https://github.com/koen666/PaperPal --skill paper-reading-quick-brief
Please help me install this Agent Skill. Skill: paper-reading-quick-brief Source: https://github.com/koen666/PaperPal/tree/main Command: npx skills add https://github.com/koen666/PaperPal --skill paper-reading-quick-brief
Paper-reading-quick-brief helps researchers quickly decide whether to deep-read a full academic paper by producing a structured decision-focused “quick brief” from the paper’s full text.
Use the skill by pasting the full paper text and adding your research focus so it can output a triage quick brief with a deep-read recommendation.
High-intent search queries and answers about installing and using this skill.
To extract the research question and methodology from a full academic paper, paste the complete text into the skill to generate a structured quick brief. This triage output consistently isolates the problem, method, and key findings for rapid review.
Yes, you can get a deep-read recommendation by providing the full paper text along with your research priorities. The skill evaluates the content and explicitly recommends whether to read in depth, including which specific sections to prioritize.
The best way to assess research relevance is to input your specific research direction alongside the paper text. The skill then rates relevance as high, medium, or low and highlights specific areas of overlap or mismatch with your work.
Yes, evidence-aware academic summarization separates explicitly stated claims from model inference. It flags missing information within the paper rather than guessing, ensuring your triage decisions rely on grounded evidence.
A key limitation of automated paper triage is that it requires the paper's complete text to function accurately. It acts as a decision-support tool for go/no-go reading rather than replacing the comprehensive understanding gained from a full deep-read.
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