Use when the user explicitly asks EZ_math_model to create defense slides, academic presentation slides, Beamer slides, or PPT after the modeling paper has been packaged.
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。
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概要と使いどころ
Use when the user explicitly asks EZ_math_model to create defense slides, academic presentation slides, Beamer slides, or PPT after the modeling paper has been packaged.
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。
Extract transcript and key slides from a local video file, then create a vault-formatted lecture note. Use this skill whenever a user provides a local video file (.mp4, .mov, .mkv, .avi, .webm) and wants notes from it. Triggers on "lecture", "take notes", "I have a recording of", "class video", "transcribe this presentation", "process this video for notes", or /lecture. Works with any language — auto-detects transcript language.
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Configure render settings, compositing nodes, output formats, and execute renders via Cycles or EEVEE engines using Python API or command-line interface. Use when automating render execution for batch processing, configuring quality and performance trade-offs, setting up compositing pipelines for post-processing, generating multiple output formats from a single render, or producing final output for publication or presentation.
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Create production-ready Grafana dashboards with reusable panels, template variables, annotations, and provisioning for version-controlled dashboard deployment. Use when creating visual representations of Prometheus, Loki, or other data source metrics, building operational dashboards for SRE teams, migrating from manual dashboard creation to version-controlled provisioning, or establishing executive-level SLO compliance reporting.
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Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks. Best for quick experiments with pre-trained models, diverse molecular representations. For ready-made ADMET numbers without training a model use admet-prediction; for benchmark datasets and task-aware splits use pytdc.
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Estimate how likely a protein therapeutic is to provoke an anti-drug antibody response, and locate the sequence regions responsible. Use this skill to tile a sequence into peptides, predict class II MHC presentation across a population-representative allele panel, aggregate predicted binders into a per-region and whole-molecule risk score, compare a candidate against its closest human germline, and decide which liabilities are worth deimmunising. Also trigger on immunogenicity, anti-drug antibody, ADA, T-cell epitope, MHC class II, HLA-DRB1, NetMHCIIpan, NetMHCpan, deimmunisation, tregitope, or population coverage.
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Protein language models through the EvolutionaryScale `esm` Python SDK. Generate and embed sequences with ESM3 (multimodal sequence, structure and function prompting), extract per-residue and mean-pooled embeddings with ESM C, fold sequences with ESMFold2, and run inference locally or against the Forge and Biohub hosted clients. Use this skill for protein representation learning, variant effect and mutational scanning from likelihoods, sequence generation and inpainting, structure prediction from sequence alone, and embedding features for downstream models. Also trigger on esm, ESM3, ESMC, ESM Cambrian, ESMFold2, `from esm.models`, ESMProtein, GenerationConfig, forge.evolutionaryscale.ai, biohub.ai, or ESM_API_KEY.
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。
Create standardized charts and visual assets from analytics query results. Prefer dependency-free plain HTML/CSS/JavaScript/SVG for interactive exploratory charts; use local plotting tools such as matplotlib, seaborn, or Plotly when static/report-ready exports or specialized charting libraries are more appropriate. Use for trends, comparisons, distributions, report assets, CSV-to-chart work, and presentation-ready data visuals.
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。
Create standardized charts and visual assets from analytics query results. Prefer dependency-free plain HTML/CSS/JavaScript/SVG for interactive exploratory charts; use local plotting tools such as matplotlib, seaborn, or Plotly when static/report-ready exports or specialized charting libraries are more appropriate. Use for trends, comparisons, distributions, report assets, CSV-to-chart work, and presentation-ready data visuals.
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。
把一个目标/主题/文章/截图/数据转成有观点、有节奏、有视觉约束的单文件 HTML 演示(网页 PPT、科技战报、产品拆解、行业观察、路演/发布会 deck、社媒可传播长图)。**7 套各锚定公认设计体系的视觉人格**——技术崇高派 Technical Sublime(工程冷光·技术战报/算力)/ 构成主义 Constructivism(宣言/号召)/ 信息·数据设计(Tufte·数据/图表)/ 判断震慑极简 Luxury(高端品牌/判断)/ De Stijl 新造型(标准/秩序)/ 编辑主义 Editorial(衬线·深度观察)/ 演示禅 Zen(暗墨·思想/品牌 keynote)——用户可指定,否则按内容自动判选并透明告知。token + validator 机检(P0/P1/P2)+ 32 维审计**机器强制设计一致性**;反伪造(不造数据/logo/截图/来源·示意标注);字体本地子集;图按角色路由(默认 CSS/SVG·要图先探测生图环境)。Generates single-file HTML decks with 7 design-system-anchored visual personas, a semantic layout grammar, locked design tokens, evidence-grading, machine validation (P0/P1/P2 + 32-dimension audit), an anti-fabrication discipline, and image-generation environment detection. Use when the user wants a presentation / deck / slides / 网页 PPT / 战报 / 产品拆解 / 行业观察 / 路演 / 发布会 / 社媒长图, or asks to turn an article / screenshot / dataset into slides. Do NOT use for large data-table training material, strict legal/medical/financial compliance documents, multi-author collaborative PPT editing, plain-text summaries, requests to replicate a brand's official keynote visuals, or any request to fabricate realistic-looking data / fake logos / fake screenshots / fake sources.
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。
Reorganize label-heavy or netlist-like electronic schematics into human-readable functional diagrams with visible local wiring while preserving proven connectivity. Use for schematic readability correction, overlapping wires or symbols, visually floating connectors or support logic, functional-sheet restructuring, bus presentation, layout annotations, or multi-EDA handoff across KiCad, Altium, EasyEDA, EAGLE/Fusion, gEDA/Lepton, SPICE/netlist, and PDF/image sources.
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。
生成"电子杂志 × 电子墨水"风格的横向翻页网页 PPT(单 HTML 文件),含 WebGL 流体背景、衬线标题 + 非衬线正文、章节幕封、数据大字报、图片网格等模板。当用户需要制作分享 / 演讲 / 发布会风格的网页 PPT,或提到"杂志风 PPT"、"horizontal swipe deck"、"editorial magazine"、"e-ink presentation"时使用。
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。
Create and edit presentation slide decks (`.pptx`) with PptxGenJS, bundled layout helpers, and render/validation utilities. Use when tasks involve building a new PowerPoint deck, recreating slides from screenshots/PDFs/reference decks, modifying slide content while preserving editable output, adding charts/diagrams/visuals, or diagnosing layout issues such as overflow, overlaps, and font substitution.
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。
Plan high-quality PowerPoint presentations before file creation or editing. Use when designing slide structure, storyline, section flow, executive summaries, local PowerPoint production briefs, Copilot prompts, or slide-review/revision prompts.
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 financial statements (income statement, balance sheet, cash flow) with period-over-period comparison and variance analysis. Use when preparing a monthly or quarterly P&L, closing the books and need to flag material variances, comparing actuals to budget, building a financial summary for leadership review, or looking up GAAP presentation requirements and period-end adjustments.
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。
Create publication-quality visualizations with Python. Use when turning query results or a DataFrame into a chart, selecting the right chart type for a trend or comparison, generating a plot for a report or presentation, or needing an interactive chart with hover and zoom.
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。
"Optimize e-commerce search relevance across the full pipeline from query understanding to result presentation. Use this skill when the user needs to improve search quality, implement query processing features, or diagnose search relevance issues — even if they say 'search results are bad', 'improve product search', or 'search relevance optimization'.".
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"Implement matrix factorization to decompose user-item interaction matrices into latent factor representations. Use this skill when the user needs scalable collaborative filtering, latent feature discovery, or dimensionality reduction for recommendation — even if they say 'SVD recommendations', 'latent factors', or 'factorize the rating matrix'.".
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。
Create or revise audience-ready HTML paper presentations for lab meetings and journal clubs. Use when Codex needs source-grounded figures and tables, a fluent live-talk narrative, verified quotations, varied explanatory diagrams, presenter-paced reveals, or browser QA for evidence fidelity, interaction, responsive layout, and print.
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。
Set up, format, fix, and clean up LaTeX regression and estimation tables in empirical economics or finance papers. Use when (a) creating a .tex, results.tex, main.tex, or preamble to display regression or estimation output from Python (pyfixest), Stata, or R — including any mention of estout, esttab, estauto, estwide, or table fragments; (b) formatting or repairing estout-style regression tables that overflow the right margin, have cramped or boxed notes, misaligned columns, or poor significance stars, or when asked to match a reference paper, make the note fill the table width, or choose among \estwide, \estauto, and landscape layouts; (c) diagnosing "Misplaced \omit" errors from \input-ed table fragments inside tabular environments. Covers \@@input, \estwide, \estauto, \estautoLT, \specialcell, \sym, minipage notes below tabulars, and the convert-and-verify workflow. Do NOT trigger for general LaTeX documents like beamer presentations, problem sets, letters, or CVs.
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。
用于将文章、演讲稿、课程、产品演示或口播解释转成可录制的 16:9 网页演示,包含步骤驱动场景、可选口播对齐、主题 Token 与录屏指导;中文触发词包括 网页视频、动态演示、口播稿转视频、可录屏演示、16:9 演示。
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。
Use when setting up or reviewing Storybook component documentation, design-system presentation, isolated component state previews, stories, addons, decorators, MDX docs, component-state interaction checks, visual baselines, or Chromatic. For real-browser cross-page journeys or broader coverage planning, choose the matching testing workflow first; Chinese triggers include Storybook, component documentation, Design System, visual regression.
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Provide constructive, evidence-based research mentoring feedback on student manuscripts, proposals, analyses, code, figures, and presentations. Use for advisor-style review that teaches the next improvement without impersonating an advisor or making unsupported scientific judgments.
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。
Comprehensive guide for visualizing ENCODE data including deeptools heatmaps, IGV screenshots, UCSC track hubs, and publication-quality plots. Use when users need to create visualizations of ChIP-seq signal, peak landscapes, genome browser views, or any visual representation of ENCODE data. Trigger on: heatmap, visualization, genome browser, track hub, IGV, deeptools, signal plot, peak visualization, profile plot, publication figure, bigWig visualization.
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。