Convert research papers into structured decision-oriented notes.
npx skills add https://github.com/yishuai778/paper-reading --skill paper-reading-yishuai778
Please help me install this Agent Skill. Skill: paper-reading Source: https://github.com/yishuai778/paper-reading/tree/main Command: npx skills add https://github.com/yishuai778/paper-reading --skill paper-reading-yishuai778
This Skill turns research papers into structured, decision-oriented notes that help users distinguish what the paper actually says from what can be reasonably inferred, enabling better trust, replication decisions, and practical use.
Read this paper and produce a decision-grade analysis with problem framing, mechanism, and actionable takeaways.
High-intent search queries and answers about installing and using this skill.
To turn research papers into structured notes, this skill separates claims, evidence, and inferences to produce decision-grade outputs that support judgments about trust, reuse, or reproduction. It frames the paper, parses the mechanism, and judges the evidence.
Yes, you can compare multiple papers using the Comparison Read and Literature Seed Map workflows. These modes analyze several papers together to help you evaluate evidence across studies and map related research domains.
The best way to evaluate evidence is to use a structured workflow that distinguishes what the paper actually says from what can be reasonably inferred. This skill frames the problem, parses the mechanism, and judges the evidence to guide implementation planning.
Yes, the skill includes an HTML Reading Page workflow that converts research papers into structured, decision-oriented notes. It produces an HTML format output to facilitate reading and evaluating the paper's claims and evidence.
You can create a reproduction memo using the dedicated workflow that converts the paper's mechanism and evidence into a judgment-ready output. This structured note specifically supports decisions about whether to replicate or reproduce the study.
Use the Quick Read mode to rapidly process the paper and produce a decision-grade analysis. This workflow extracts problem framing, mechanism details, and actionable takeaways without deep parsing.
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