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概要と使いどころ
Use when adding hypermedia links to REST responses, building self-describing APIs, or implementing Spring HATEOAS. Use when you see EntityModel, CollectionModel, or RepresentationModel in the project.
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。
Launch, inspect, or tear down an isolated fleet of ready SDD Composy tasks: one branch and Git worktree per member, a bound LOOP, cmux/tmux/headless presentation, no automatic merge. Use to run several ready tasks in parallel — 'rodar várias tarefas em paralelo', 'lançar o fleet', 'fleet status', 'tear down member X'. Do NOT use for a single task (sdd-execute, sdd-loop) or for merging without the explicit teardown token.
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 any visual design using Adobe Express templates — including flyers, posters, banners, social media posts (Instagram stories, Facebook posts, LinkedIn graphics), business cards, invitations, greeting cards, resumes, cover letters, brochures, newsletters, certificates, presentations, YouTube thumbnails, email headers, logos, menus, labels, and more. Use this skill whenever the user wants to make, design, create, or build any visual — even if they just say "make me a flyer", "design a poster", "I need something for Instagram", "create an event invite", "make a business card", or any similar request. Also handles requests to find or browse templates, edit text/copy, change background colors, or animate a design. Access: 🔐 Signed-In required | Gen AI: ❌
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。
Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.
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。
Implement EUI sessions, shared state and messages, server lifecycle, and client presentation.
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。
Place contracts and behavior across authority, prediction, presentation, localization, and assembly boundaries.
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。
Resolve localized text at presentation boundaries using English-source keys, with Russian localization only when requested, and correct lifecycle refresh.
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 this skill when the user requests to generate, create, or make presentations (PPT/PPTX). Creates visually rich slides by generating images for each slide and composing them into a PowerPoint 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。
Generate PPTX presentations, DOCX documents, XLSX spreadsheets, and PDF reports from structured JSON input using PaperJSX.
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。
Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.
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。
Predict peptide-MHC class II (HLA-DR/DQ/DP) binding and presentation for CD4 T-cell epitopes with NetMHCIIpan-4.3 and MixMHC2pred-2.0. Covers why class II is far less reliable than class I (open binding groove, 9-mer register ambiguity, sparse noisy training data, DR>DP>DQ accuracy asymmetry), the DQ/DP heterodimer alpha/beta pairing trap, and the looser 1%/5% %Rank thresholds. Use when predicting CD4 epitopes for vaccine help, mapping class II neoantigens, or scoring long peptides against DR/DQ/DP. For CD8/class I see mhc-binding-prediction.
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。
Quality control for pooled CRISPR screens covering library representation, Gini index, log-skew, replicate Pearson and Spearman concordance, essentialome precision-recall AUC against CEGv2 (Hart 2017), Cas9 cut-toxicity diagnostics, copy-number amplicon detection (Aguirre 2016 / Munoz 2016), bottleneck propagation through plasmid pool, infection, selection, and endpoint stages, MOI verification, and DepMap-style screen-quality scoring. Use when assessing screen quality before hit calling, deciding whether to repeat or rescue a screen, diagnosing low-confidence hits, choosing between MAGeCK / BAGEL2 / Chronos based on quality grade, picking a normalization strategy from QC signatures, or evaluating whether an in-vivo screen retained adequate library complexity.
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。
Build publication-quality figures in R with ggplot2 using the grammar of graphics (data + aesthetics + geometries + scales + facets + themes) with CVD-safe palettes, cairo_pdf TrueType embedding, programmatic aes via tidy evaluation, and the theme_classic publication baseline. Use when producing static figures in R for papers, presentations, or reports.
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。
Resolves rsIDs, navigates RsMergeArch/SNPHistory merge chains, and converts between rsID, SPDI, HGVS, and VCF representations using the dbSNP Build 156 JSON architecture. Use when normalizing variant identifiers, joining variant databases by cluster ID, or tracking deprecated rsIDs through historical merges.
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。
Structure any communication artifact — documents, reports, plans, issue comments, PR descriptions, emails, presentations, slides, charts, and dashboards — using Jean-luc Doumont's "Trees, Maps, and Theorems" method. Use whenever the goal is to get a message across to a busy audience, when asked to improve clarity or structure of writing or slides, or when a deliverable will be judged by whether readers act on it, not just read it.
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。
Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.
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。
After-Action Review—structured debrief asking what was expected, what happened, why the difference, and what next. Use after projects, launches, presentations, or any significant event.
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 this skill when the user requests to generate, create, or make presentations (PPT/PPTX). Creates visually rich slides by generating images for each slide and composing them into a PowerPoint 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。
Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.
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 a Python CLI tool for bidirectional conversion between 4-byte floating-point numbers and hexadecimal memory representations, featuring a continuous loop and robust input parsing.
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。
Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.
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 professional slide deck images from content. Creates outlines with style instructions, then generates individual slide images. Use when user asks to "create slides", "make a presentation", "generate deck", "slide deck", or "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。
Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.
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。