Paper Analyzer

学术论文结构化阅读、拆解与分析工具。基于12个阅读要素（研究背景、研究问题、研究结论、文献综合、文献批评、研究方法、理论视角与理论框架、一致性发现、不一致性发现、研究贡献、研究不足、未来研究展望）对论文进行深度拆解，结果保存为Excel文件。当用户提到需要针对论文/文献/paper进行拆解、解析、分析、阅读、梳理...

This skill appears coherent and low-risk, but check a few things before use: (1) Inspect scripts/export_excel.py yourself (it's included) to confirm behavior—it's straightforward and only writes Excel files. (2) Ensure your agent environment has Python3 and the openpyxl package (and pdftotext if you plan to rely on it); missing dependencies will cause runtime errors. (3) Be mindful that the skill will read any local files you point it to and will save Excel files into the same folder (risk of overwriting). Don’t feed documents containing secrets or sensitive data unless you are comfortable with local processing. (4) If you plan to let the agent invoke skills autonomously, remember this skill will have access to any local file paths you provide at runtime. If you want greater assurance, run the export script manually on sample JSON to confirm outputs before granting the agent broad file access.

Type: OpenClaw Skill Name: paper-analyzer Version: 1.0.0 The 'paper-analyzer' skill is designed to extract structured information from academic papers (PDF/Word) and export the analysis to Excel files. The workflow involves reading local files, processing text via standard tools like 'pdftotext', and executing a local Python script (scripts/export_excel.py) to generate formatted spreadsheets. There is no evidence of data exfiltration, unauthorized network access, or malicious prompt injection; the code and instructions are strictly aligned with the stated purpose of academic document analysis.