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Self-learning
Self-learning contiene 43 skills recopiladas de photonics-dhl, con cobertura ocupacional por repositorio y páginas de detalle dentro del sitio.
Skills en este repositorio
填写 Word (.docx) 表格表单,格式零破坏。完整流程: 1. 用 python-docx 深度解析文档结构(段落/表格/合并单元格/表单域) 2. 定位可填写区域(区分指引行 vs. 内容行) 3. 保留原始格式(rPr/pPr)写入内容 4. 备份原文件 → 写入 → 验证 → Humanizer 润色 触发场景: - 明确填写类:"帮我填表"、"填写申请表"、"填写 Word 表单"、"填这个 docx" - 修改内容类:"修改这个表格"、"在这个 docx 里填入"、"更新 Word 表格内容" - 批量操作类:"批量填表"、"把这些信息填到表格里"、"生成填写好的 Word 文档" - 文件路径指向 .docx 且语境为填写/修改/填入内容 - 提到"表格"、"表单"、"申请表"且目标文件是 Word 格式 - 任何需要在 .docx 表格中写入内容且保持格式的场景 依赖:python-docx(pip install python-docx)
审稿人专用技能。当用户提到以下任何场景时必须自动触发: - "审稿"、"审稿意见"、"审稿信"、"写审稿意见"、"帮我看这篇论文作为审稿人" - "review this paper"、"referee report"、"peer review" - "评价这篇稿件"、"给这篇论文写审稿意见"、"作为审稿人" - 收到期刊审稿邀请、需要提交审稿报告 7阶段系统化审稿流程(初评→逐节→统计→可复现→图表→研究诚信→写作质量)。 生成中英双语标准审稿信,含物理/光学实验特有审查项。 注意:本 skill 是"审别人的论文",不是自审(paper-review)也不是写作诊断(academic-craft)。
学术写作诊断与修订。对已完成的文献综述或论文草稿进行6维度质量诊断,输出具体修订方案。适用于任何学术写作的质量把关。
Advanced diagram generation skill supporting DrawIO, Mermaid, and Excalidraw formats for creating professional technical diagrams. **Trigger when**: User says "生成图表", "DrawIO", "excalidraw", "专业技术图", "architecture diagram", "系统架构图", "wireframe" **Also trigger when**: User wants: - Professional architecture diagrams - UML diagrams with more detail than Mermaid - Interactive diagrams (Excalidraw) - Technical drawings with precise shapes - Network diagrams - UI wireframes **DO NOT trigger for**: Simple flowcharts (use mermaid), photo-realistic images (use image-generation). Make sure to use this skill when the user needs more sophisticated diagrams than Mermaid can provide, or when they specifically request DrawIO/Excalidraw format.
系统性文献综述撰写。整合 Pautasso (2013) 综述写作规则和 C-C-C 结构原则。当用户需要写文献综述时触发。
光学学习技能,提供知识树构建、概念可视化和学习进度跟踪。 触发条件: - 用户说"帮我梳理XX知识体系" - 用户说"构建XX的学习路径" - 用户说"我需要学习超表面光学" - 用户询问某个光学概念的前置知识 自动触发:当用户表达学习光学领域知识的需求时。
学术论文搜索技能,集成多个学术数据库进行文献发现。 触发条件: - 用户需要搜索特定论文 - 用户需要查找某领域的代表性文献 - 用户需要按 DOI/标题查找论文 核心能力: - PubMed / ArXiv / Semantic Scholar 联合搜索 - 按标题匹配查找论文 - 获取论文引用和参考文献
科研写作工艺——段落/语言层面的写作工具。两阶段写作流程、段落清晰度检查、反向大纲、7条全局原则、段落角色标注、Claim-Evidence映射。当用户需要优化段落质量、改善逻辑流、做语言层面润色时触发。不负责论文结构规划(那是paper-writing)。
文档处理技能集(增强版)。支持多格式输入转换、PDF操作、Office文档创建/编辑。 输入:PDF, DOCX, XLSX, PPTX, HTML, EPUB, CSV, JSON, 图片(OCR), 音频(转录)。 输出:Markdown, DOCX, PPTX, XLSX, PDF。 基于 K-Dense markitdown/pdf/docx/pptx/xlsx/liteparse skills 增强。
Search 78 public scientific, biomedical, materials science, and economic databases via REST APIs. Covers physics/astronomy (NASA, NIST, SDSS, SIMBAD), earth/environment (USGS, NOAA, EPA), chemistry/drugs (PubChem, ChEMBL, DrugBank, FDA, KEGG, ZINC, BindingDB), materials (Materials Project, COD), biology/genomics (Reactome, UniProt, STRING, Ensembl, NCBI Gene, GEO, GTEx, PDB, AlphaFold, InterPro, BioGRID, Gene Ontology, dbSNP, gnomAD, ENCODE, Human Protein Atlas, Human Cell Atlas), disease/clinical (COSMIC, Open Targets, ClinicalTrials.gov, OMIM, ClinVar, GDC/TCGA, cBioPortal, DisGeNET, GWAS Catalog), regulatory (FDA, USPTO, SEC EDGAR), economics/finance (FRED, World Bank, US Treasury), demographics (US Census, Eurostat, WHO). Use when looking up compounds, genes, proteins, pathways, variants, clinical trials, patents, economic indicators, or any public database API query.
Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Support for conference presentations, academic posters, and scientific communication. Includes layout design, color schemes, multi-column formats, figure integration, and poster-specific best practices for visual communication.
Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal styling, use scientific-visualization.
Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
Quantum physics simulation library for open quantum systems. Use when studying master equations, Lindblad dynamics, decoherence, quantum optics, or cavity QED. Best for physics research, open system dynamics, and educational simulations. NOT for circuit-based quantum computing—use qiskit, cirq, or pennylane for quantum algorithms and hardware execution.
Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design templates, timing guidance, and visual validation. Works with PowerPoint and LaTeX Beamer.
Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.
Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.
Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.
Use when you need exact symbolic math in Python — algebra, calculus, equation solving, symbolic linear algebra, or code generation via lambdify/LaTeX. Prefer NumPy or SciPy when floating-point approximations are sufficient.
Access comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues (Nature, Science, PLOS, IEEE, ACM), academic conferences (NeurIPS, ICML, CVPR, CHI), research posters, and grant proposals (NSF, NIH, DOE, DARPA). This skill should be used when preparing manuscripts for journal submission, conference papers, research posters, or grant proposals and need venue-specific formatting requirements and templates.
LaTeX (ctexart) → DOCX 格式保持转换。三步流程: 1. python-docx 生成匹配 ctexart 样式的 reference.docx 模板 2. pandoc + reference.docx 执行转换(公式→OMML、图片嵌入) 3. python-docx 后处理(中文字体、图注识别、表格线型、图片尺寸) 触发场景: - 用户需要将 LaTeX 文件转为 Word 文档并保持格式 - 用户说"转 docx"、"输出 Word 版本"、"转成 Word" - 中期报告、论文等需要提交 DOCX 格式时 依赖:python-docx、pandoc 3.x
智能学术研究技能 v2.0 - 数据驱动的可验证文献综述生成 触发条件: - 用户需要文献调研并生成可验证的学术综述 - 用户需要"帮我写一篇关于X的综述" - 用户需要基于真实文献的LaTeX论文 核心工作流: 1. OpenAlex 论文发现(按相关性排序) 2. 多字段关键词分组(PCA/OR/等离子体/超表面等) 3. LaTeX + BibTeX 导出 4. 引用图谱生成 数据保证:所有论文信息(作者/年份/期刊/引用数/DOI)均来自真实API响应, 摘要从 inverted_index 重建,数值可溯源。
中文学术毕业论文(本科/硕士/博士)全流程写作指导与质量检查 Skill。 用于辅助毕业论文的撰写、修改、审查与定稿,覆盖写作风格、文献检索、 论文结构规范、排版语法、实验规范、盲审合规性、图表一致性等维度。 使用场景: (1) 撰写或修改论文章节内容时,确保符合学术写作规范 (2) 润色文本,去除 AI 写作痕迹,使行文自然如人类研究者亲笔 (3) 检索、筛选和管理学术参考文献 (4) 检查论文结构、逻辑一致性、盲审匿名性、图表风格一致性 (5) 定稿前的全面复盘检查
博士/硕士中期考核进展报告撰写流程。从材料索引→RAG检索→Markdown撰写→质量检查→LaTeX转换的完整pipeline。
学术写作诊断与修订。对已完成的文献综述或论文草稿进行6维度质量诊断,输出具体修订方案。适用于任何学术写作的质量把关。
智能学术研究技能 v2.0 - 数据驱动的可验证文献综述生成 触发条件: - 用户需要文献调研并生成可验证的学术综述 - 用户需要"帮我写一篇关于X的综述" - 用户需要基于真实文献的LaTeX论文 核心工作流: 1. OpenAlex 论文发现(按相关性排序) 2. 多字段关键词分组(PCA/OR/等离子体/超表面等) 3. LaTeX + BibTeX 导出 4. 引用图谱生成 数据保证:所有论文信息(作者/年份/期刊/引用数/DOI)均来自真实API响应, 摘要从 inverted_index 重建,数值可溯源。
Advanced diagram generation skill supporting DrawIO, Mermaid, and Excalidraw formats for creating professional technical diagrams. **Trigger when**: User says "生成图表", "DrawIO", "excalidraw", "专业技术图", "architecture diagram", "系统架构图", "wireframe" **Also trigger when**: User wants: - Professional architecture diagrams - UML diagrams with more detail than Mermaid - Interactive diagrams (Excalidraw) - Technical drawings with precise shapes - Network diagrams - UI wireframes **DO NOT trigger for**: Simple flowcharts (use mermaid), photo-realistic images (use image-generation). Make sure to use this skill when the user needs more sophisticated diagrams than Mermaid can provide, or when they specifically request DrawIO/Excalidraw format.
文档处理技能集。用于处理 Word (docx)、PDF、PowerPoint (pptx)、Excel (xlsx) 等办公文档。 当用户需要创建、编辑、分析文档时触发。 包含完整的文档创建规范、样式指南、公式验证等。
系统性文献综述撰写。整合 Pautasso (2013) 综述写作规则和 C-C-C 结构原则。当用户需要写文献综述时触发。
光学学习技能,提供知识树构建、概念可视化和学习进度跟踪。 触发条件: - 用户说"帮我梳理XX知识体系" - 用户说"构建XX的学习路径" - 用户说"我需要学习超表面光学" - 用户询问某个光学概念的前置知识 自动触发:当用户表达学习光学领域知识的需求时。
学术论文搜索技能,集成多个学术数据库进行文献发现。 触发条件: - 用户需要搜索特定论文 - 用户需要查找某领域的代表性文献 - 用户需要按 DOI/标题查找论文 核心能力: - PubMed / ArXiv / Semantic Scholar 联合搜索 - 按标题匹配查找论文 - 获取论文引用和参考文献
科研写作工艺——段落/语言层面的写作工具。两阶段写作流程、段落清晰度检查、反向大纲、7条全局原则、段落角色标注、Claim-Evidence映射。当用户需要优化段落质量、改善逻辑流、做语言层面润色时触发。不负责论文结构规划(那是paper-writing)。
英文期刊论文AI辅助撰写。从Gap识别到定稿的全流程pipeline,整合三源文献、Gap-driven规划、审稿人友好写作、反AI痕迹。当用户需要写英文期刊论文时触发。中文毕业论文请用bishe-guider。
已合并到 paper-writing 和 scientific-writing。保留此文件用于向后兼容路由。
消除文本中AI生成的痕迹,使其听起来更自然、更像人类写作。当用户需要润色论文、去AI味、改写段落时触发。
笔记创建前的知识规划。扫描同级目录、分析关系、输出规划卡,防止重复笔记。写任何笔记前强制执行。
笔记因果链和四层理解模型。定义笔记间的逻辑关系(前提→核心→推导→应用)。
双代理协作的论文质量审查系统。检查期刊格式规范、学术质量、图表一致性。当用户需要审查论文时触发。
Mermaid diagram generation skill for creating knowledge trees, flowcharts, sequence diagrams, and concept visualizations. **Trigger when**: User says "生成图表", "画个图", "mermaid", "知识树", "流程图", "生成mermaid", "画流程图", "knowledge graph", "flowchart" **Also trigger when**: User wants to visualize: - Concept relationships (knowledge trees) - Process flows (workflows, procedures) - System architecture - State machines - Entity relationships - Sequence/timeline diagrams **DO NOT trigger for**: Complex 3D visualizations (use image-generation), detailed technical drawings (use diagram-generator or image-generation). Make sure to use this skill whenever the user wants to visualize relationships, processes, or structures. Mermaid is free and fast - prefer it over image-generation for simple diagrams.