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概要と使いどころ
Generate beautiful interactive timeline HTML pages from JSON data, with vertical, horizontal, or dual-side layouts, collapsible details, and custom colors. Ideal for project milestones, company histories, or resumes. Triggered when a user mentions 'timeline', 'history of events', 'project milestones', 'release log', or asks to visualize a chronological sequence of data.
日本語の概要は準備中です。原文の説明を表示しています。
Generate self-contained HTML/SVG infographics from JSON data, including stat cards, bar charts, flow diagrams, and mixed dashboards. Offers 8 color palettes and built-in icons with no external dependencies. Triggered when users request data visualization, infographics, charts, or dashboards.
日本語の概要は準備中です。原文の説明を表示しています。
English LaTeX academic paper assistant for existing `.tex` projects. Use this skill whenever the user wants to compile, lint, audit, or improve an English LaTeX conference or journal paper such as IEEE, ACM, Springer, NeurIPS, or ICML submissions. Trigger even when the user only mentions one paper issue, such as bibliography errors, grammar cleanup, sentence splitting, logic review, expression polishing, translation, title optimization, figure checks, pseudocode review, algorithm block cleanup, de-AI editing, experiment-section review, table structure validation, three-line table generation, abstract structure diagnosis, or journal adaptation. Also trigger for "proofread my paper", "fix my LaTeX", "prepare for submission", "check my manuscript", "improve my writing", "three-line table", "booktabs", "check abstract", "reformat for another journal", "换投", `algorithm2e`, `algorithmicx`, `algpseudocodex`, `Require/Ensure`, or "Algorithm 1" when the user has a .tex file.
日本語の概要は準備中です。原文の説明を表示しています。
Cleans a Quarto (.qmd) file by replacing LaTeX holdovers with proper Quarto/Pandoc syntax so the document renders correctly to HTML, PDF (Typst/LaTeX), and Word. Fixes citations (\citep → [@key]), cross-references (\ref → @label), figures (\includegraphics → markdown), tables, text formatting (\textbf → **bold**), inline math (\( \) → $ $), hyperlinks (\href → [text](url)), footnotes (\footnote → ^[]), list environments, section headings, and R Markdown chunk options (dot-style → #| YAML). Use when asked to clean, fix, modernize, or port a Quarto or R Markdown document; when LaTeX commands appear in a .qmd file; when a document fails to render to Word or Typst; or when citations/cross-references do not appear in non-LaTeX output.
日本語の概要は準備中です。原文の説明を表示しています。
Econometrics skill for machine learning methods in causal inference. Activates when the user asks about: "causal forest", "generalized random forest", "GRF", "double machine learning", "DML", "debiased machine learning", "LASSO for variable selection", "post-LASSO", "heterogeneous treatment effects", "CATE", "conditional average treatment effect", "BLP analysis", "CLAN analysis", "causal tree", "honest estimation", "因果森林", "双重机器学习", "异质性处理效应", "条件平均处理效应", "LASSO变量选择", "机器学习因果推断", "去偏机器学习"
日本語の概要は準備中です。原文の説明を表示しています。
Export Marp slide markdown files to PDF (default), HTML, PPTX, or PNG. Handles theme loading, Chrome/Chromium detection for PDF export, and batch conversion. Trigger when user says "export slides", "convert marp to pdf", "marp export", "slides to pdf", "slides to html", "导出slides", "slides转pdf", "导出演示文稿".
日本語の概要は準備中です。原文の説明を表示しています。
Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.
日本語の概要は準備中です。原文の説明を表示しています。
Add descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions added to prod.yaml and dev.yaml. Triggers on requests like "add new model descriptions", "update models from router", "sync models", or when explicitly invoking /add-model-descriptions.
日本語の概要は準備中です。原文の説明を表示しています。
Show an HTML chart, table, diagram, mockup, demo, or report inline in BB chat: write a small page directly in the reply as an inline-vis fenced block, or show a workspace or thread-storage HTML or Markdown file with the inline-vis directive.
日本語の概要は準備中です。原文の説明を表示しています。
Track and synthesize current AI hotspots into a bilingual HTML daily report. Use when the user says "AI热点", asks for AI日报/AI日报 HTML/AI hot topics, or wants the best recent AI products, papers, viewpoints, and cognition-shifting items from AI/news aggregators.
日本語の概要は準備中です。原文の説明を表示しています。
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）。
日本語の概要は準備中です。原文の説明を表示しています。
International / multilingual SEO audit focused on hreflang correctness: missing or broken return tags, wrong language/region codes, missing x-default, self-referencing errors, hreflang vs canonical conflicts, and inconsistent signals across HTML head, HTTP headers and XML sitemap. Also reviews URL structure (ccTLD vs subdirectory vs subdomain), language targeting and geo signals. Use whenever the user runs a multi-language or multi-region site and asks about hreflang, international or multilingual SEO, the wrong-language page showing in search, or duplicate content across country versions. Trigger on: "hreflang", "international SEO", "multilingual SEO", "multi-region", "wrong language in Google", "x-default", "ccTLD vs subdirectory", "geo targeting", "language targeting", "my English page shows for Thai users", "th/en page ranking in the wrong country", or any cross-language/cross-country ranking question. For full-site audits use /seo-analysis; for a single URL use /seo-page.
日本語の概要は準備中です。原文の説明を表示しています。
Split datasets into training, validation, and test partitions with the right stratification and temporal rules. Use as a narrow preprocessing helper once the broader ML workflow is already chosen, not as the main route owner for an end-to-end ML task.
日本語の概要は準備中です。原文の説明を表示しています。
Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard - Google's ML visualization toolkit
日本語の概要は準備中です。原文の説明を表示しています。
Computational pathology toolkit for analyzing whole-slide images (WSI) and multiparametric imaging data. Use this skill when working with histopathology slides, H&E stained images, multiplex immunofluorescence (CODEX, Vectra), spatial proteomics, nucleus detection/segmentation, tissue graph construction, or training ML models on pathology data. Supports 160+ slide formats including Aperio SVS, NDPI, DICOM, OME-TIFF for digital pathology workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Detects and prevents data leakage in machine learning and mathematical modeling. Use after ML tasks involving data cleaning, feature engineering, data augmentation, algorithm development, normalization, missing value imputation, dimensionality reduction, feature selection, or time series modeling. Checks if features/statistics would be available at prediction time.
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
日本語の概要は準備中です。原文の説明を表示しています。
Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.
日本語の概要は準備中です。原文の説明を表示しています。
Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.
日本語の概要は準備中です。原文の説明を表示しています。
Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.
日本語の概要は準備中です。原文の説明を表示しています。
把 Markdown 文稿排版并转换为 HTML、可打印 PDF 或长图 PNG。当用户说“Markdown/MD 转 HTML/PDF/图片、文章导出长图、MD 排版/渲染”时使用。仅处理 Markdown；DOCX/PPT 不在范围内，层级大纲转脑图用 mindmap。
日本語の概要は準備中です。原文の説明を表示しています。
思维导图：把 Markdown 大纲（标题层级 + 列表）渲染成可交互思维导图 HTML，可选导出 PNG。适合知识结构、内容框架、SWOT、脑图梳理。当用户说 思维导图、脑图、mindmap、知识导图、大纲图、把要点做成脑图、内容结构图、SWOT图、树状图 时使用。基于 shared/scripts/mindmap.py（markmap 自包含 HTML + Chromium 渲染 PNG）。与 chart-visualization/infographic 区别：那些做数据图表/信息图，本 SKILL 专做层级大纲思维导图。
日本語の概要は準備中です。原文の説明を表示しています。
微信公众号文章排版引擎：把 Markdown / Word(.docx) / PDF / 纯文本转成可直接粘贴进公众号编辑器的 HTML，自动章节编号、关键词标记、引言卡、目录、代码块、图片/GIF、作者签名；主题从 references/theme-index.md 组件库按题材推荐，支持"一键自动排版"与按描述/参考图生成自定义主题。触发：用户提到"公众号排版/微信排版/gzh"、想把文章(md/docx/pdf/纯文本)转成公众号 HTML、说"自动排版/一键排版"公众号内容。不用于普通网页/落地页/PPT。
日本語の概要は準備中です。原文の説明を表示しています。
Run Megatron-LM (MLM) and Megatron Bridge training with mock or real data. Covers correlation testing, available recipes, and multi-GPU examples.
日本語の概要は準備中です。原文の説明を表示しています。