xray-paper-skill_skill

Overview

This skill deconstructs academic papers into their core contributions, hidden assumptions, and easily communicated insights. It does not simply summarize; it breaks the paper’s logical model into discrete components and produces a compact, actionable report suitable for researchers and practitioners. The output includes a five-dimension analysis and an ASCII logic flow diagram for quick mental mapping.

How this skill works

The skill ingests a paper from a provided PDF, text block, or URL and applies a reproducible cognitive extraction algorithm. It denoises the text, extracts claims and supporting evidence, performs targeted critiques, and synthesizes a napkin-worthy formula or sketch. The final report follows a fixed template and includes timestamped output and an ASCII flow that visualizes the argument structure.

When to use it

• You need to understand the paper’s underlying logic beyond surface summaries.
• Preparing a literature review and need crisp statements of contribution and limitations.
• Evaluating whether a paper’s assumptions or experimental design fit your project.
• Distilling complex methods into a simple, reproducible sketch for discussion.
• Converting academic results into quick, implementable rules or heuristics.

Best practices

• Provide the full paper text or a high-quality PDF for best extraction accuracy.
• Point out specific sections (e.g., methods, experiments) when you want focused critique.
• Use short keywords for the short-title to generate tidy, searchable filenames.
• Verify automated critiques against the original paper before acting on them.
• Combine outputs with your notes to build reproducible, shareable summaries.

Example use cases

• Rapidly decide if a new model paper is relevant to your project by reading the Problem/Delta summary.
• Prepare a one-slide summary for a lab meeting showing Insight, Critique, and Napkin Formula.
• Audit a paper’s assumptions before attempting replication or adaptation.
• Generate a concise critique for peer review or class discussion.
• Translate experimental claims into concrete checks to run on your own data.