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zLanqing
GitHub 创作者资料

zLanqing

按仓库查看 1 个 GitHub 仓库中的 4 个已收集 skills,并展示近似职业覆盖。

已收集 skills
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1
职业领域
2
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2026-05-14
职业覆盖
该创作者主要覆盖的职业大类。
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仓库与代表性 skills

#001
codex-claude-academic-skills
4 个 skills23116更新于 2026-05-14
占该创作者 100%
office-academic-skill
高等院校职业/技术教育教师

Chinese-first academic Word and PowerPoint workflow for paper reading reports, thesis or group-meeting PPTs, editable DOCX/PPTX generation, Office file inspection, template matching, speaker notes, and layout quality checks. Use when the user asks to read papers into Word reports, create or polish PPT/PPTX, convert paper/thesis materials into slides, edit DOCX/PPTX, inspect Office files, or produce Chinese academic presentation/report deliverables. Preserve English paper titles, formulas, variable names, software commands, and references.

2026-05-14
research-writing-skill
其他高等院校社会科学教师

Chinese-first research paper writing, revision, polishing, section drafting, rebuttal, peer-review response, thesis prose improvement, and manuscript argument planning. Use when the user asks to write or revise论文正文, abstracts, introductions, methods, results, discussion, conclusions, related work, responses to reviewers, LaTeX/Overleaf text, or academic prose. Preserve formulas, English paper titles, terms, citations, and measured results.

2026-05-14
literature-review
高等院校大气、地球、海洋和空间科学教师

Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).

2026-05-14
scientific-toolkit-skill
数据科学家

Research computing toolkit for optoelectronic information science and engineering, MATLAB/Octave, Python scientific analysis, signal processing, image processing, statistics, simulation, optimization, publication figures, sensor/time-series data, citation lookup, and common scientific libraries. Use when the user asks for MATLAB code, scientific Python, data analysis, plots, simulations, formulas, statistics, machine learning, optical/physical/materials computation, or reproducible research workflows.

2026-05-14
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