video-frames
Extract frames or short clips from videos using ffmpeg.
Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Extract frames or short clips from videos using ffmpeg.
This skill should be used when the user asks to "create a math animation", "animate a mathematical concept", "generate Manim code", "visualize [topic] with animation", "explain [concept] visually", "create an educational video", "build a Manim scene", or mentions "reverse knowledge tree", "prerequisite discovery", or "verbose prompt generation". Provides a complete six-agent workflow for transforming any concept into professional Manim animations through recursive prerequisite discovery.
微信公众号文章排版引擎,将 Markdown 转换为可直接粘贴到公众号编辑器的 HTML。主题风格从 references/theme-index.md 注册的自定义主题库中选取,自动章节编号、关键词下划线标记、引言卡片、目录导航、代码块、图片/GIF、作者签名。支持 Markdown / Word(.docx) / PDF / 纯文本输入(非 Markdown 先自动归一化),也支持"一键自动排版"(自动推断结构+选主题),还支持根据用户描述/参考图生成自定义主题组件库并保存本地复用。触发场景:(1) 用户提到"公众号排版""公众号文章""微信排版""gzh",(2) 用户想把文章(md/docx/pdf/纯文本)转成公众号 HTML,(3) 用户说"自动排版""一键排版"公众号内容,(4) 用户想为公众号排版"生成新主题/自定义风格/按这张图做一套组件库"。不用于生成普通网页/落地页/PPT(用前端或 PPT 类 skill)。
Umbrella skill for document workflows (PDF/DOCX/XLSX/PPTX). Dispatches to the most specific document skill to reduce noise and improve routing precision.
Reply to comments (批注) in Word .docx/.doc files: extract comment context, draft replies, write threaded replies back, and validate OOXML.
Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.
⚠️ CRITICAL USER EXPERIENCE-BASED SKILL - ALWAYS CONSULT BEFORE DATA PREPROCESSING ⚠️ Prevents catastrophic errors (88.9% error rate in V1.0 case study) through multi-level feature analysis, data leakage detection, and semantic validation. MANDATORY for: data preprocessing, feature engineering, standardization, normalization, interpolation, missing value handling, feature selection, or ANY data transformation task. Covers grouped time-series, cross-sectional, panel data. Detects: time travel leakage, causal inversion, ID misuse, semantic-numeric fallacies, distribution blindness. User's hard-won lessons from real project failures.
Build research slides with text-first source (Slidev/Marp/Reveal/Quarto) and reproducible export (PDF). Includes structure, figure reuse rules, and quality checklist for top-tier scientific presentations.
Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that do not fit in memory.