747 件 ・ 関連度順
概要と使いどころ
Draft professional emails for various contexts including business, technical, and customer communication. Use when the user needs help writing emails or composing professional messages.
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。
Multi-Omics Factor Analysis v2 (MOFA+) with mofapy2. Jointly decompose omics layers (scRNA, ATAC, proteomics, methylation) into latent factors capturing major variation. Multi-group designs. AnnData views → MOFA object → train → variance explained → correlate factors with metadata → visualize/cluster → enrich top loadings.
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。
Assemble multiple plots into ONE publication-ready multi-panel journal figure (e.g. Figure 1 with panels A, B, C). Use whenever the user asks to combine, compose, or lay out several plots as a single composite figure — newly plotted from data or from already-rendered panels the user supplies (PNG/PDF). Ask the user to pick one of two approaches: (1) redraw every panel into one unified figure using independent, tightly packed `subfigures` (each sized to its own labels, so axes need NOT align), consistent style, correctly placed panel letters, and per-panel legends/colorbars; (2) composite already-rendered PNG/PDF panels onto a mosaic canvas and add panel letters (image compositing, not plotting). Both export vector PDF + high-DPI PNG. For a SINGLE plot from a data table, use the sibling `omics-plotting` skill instead.
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。
Read, decompose, and analyze IEEE-style papers using routed technical-reading workflows. Use when extracting problem setting, object-method-condition logic, contributions, method pipeline, equations, datasets, baselines, metrics, ablations, limitations, replication details, citation role, related-work positioning, implementation notes, or reviewer-style assessment from a paper, PDF, abstract, or manuscript excerpt.
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。
Creates and scaffolds a new Spring Boot project (3.x or 4.x) by downloading from Spring Initializr, generating package structure (DDD or Layered architecture), configuring JPA, SpringDoc OpenAPI, and Docker Compose services (PostgreSQL, Redis, MongoDB). Use when creating a new Java Spring Boot project from scratch, bootstrapping a microservice, or initializing a backend application.
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。
Break down CWICR work items into component resources. Decompose aggregate items, analyze resource composition, and generate detailed bills of resources.
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。
Remotion + Kling i2v でプロモーションMV動画・バイラルショート動画を生成するスキル。 「MV作成」「動画を作って」「プロモーション動画」「TikTok動画」等のリクエストで発動。
Create production-quality Android applications following Google's official architecture guidance and NowInAndroid best practices. Use when building Android apps with Kotlin, Jetpack Compose, MVVM architecture, Hilt dependency injection, Room database, or multi-module projects. Triggers on requests to create Android projects, screens, ViewModels, repositories, feature modules, or when asked about Android architecture patterns.
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。
Decompose a session into typed handoff units and recall them later. Use when ending a session or resuming work whose prior state must be recovered.
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。
CHAIN multiple existing skills into custom multi-step workflows. Programmable skill combinations with automatic handoffs. Create composite skills from building blocks with conditional logic.
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。
Casual but professional tone for team communication. Uses company-specific terminology with scannable format.
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。
Debug Docker containers, fix Dockerfile issues, optimize images, and troubleshoot docker-compose. Use when having Docker problems, container issues, or optimizing Docker builds.
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 DeepMind dm_control for MuJoCo simulation, Control Suite environments, PyMJCF models, Composer tasks, rendering, and high-level locomotion/manipulation 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。
Generate screenshot coverage for screen-level Compose previews from the current diff or a specific target, check required visual and data variations, and produce a compact visual report
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。
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability.
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。
Preserve the coding agent's explicit AAS skill selection as a validated stack and optional evidence.
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。
Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.
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。
小红书 / 抖音 / 快手 / 视频号 自媒体「(compose 素材打底 →) 找对标 → 拆爆款 → 套自己」四命令闭环，另支持带货账号诊断、带货视频链接拆解和证据驱动的脚本生成（commerce）。给账号 / 平台视频链接 / 本地视频 / 商品详情、SKU 与资质材料，输出账号与对标差距、内容拆解、商品事实卡、口播和分镜。当用户说"找对标"、"拆这条爆款"、"对着这条仿写"、"下一条该写什么"、"我这个号缺爆款选题"、"帮我写一条对标 XX 的笔记"、"我有素材帮我写一条能爆的"、"这份文档/这组图/这段视频能出一条爆款吗"时调用。诊断模式（"为什么不爆"）走 references/diagnostic-mode.md。带货触发词：带货账号诊断、带货视频链接、带货素材、商品详情截图、SKU 表、商品资质、带货脚本、口播、分镜、商品卡一致性 — 走 commerce 路由。商品链接不等于视频链接；本 Skill 不解析在线商品页，不提供选品、趋势监控或 GMV/佣金推断。
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。
Conduct deep web research using the openbrowser-ai agent: decompose a query, investigate sub-questions across multiple sources, and produce a cited markdown report plus structured JSON under local_docs/research/. Trigger when the user asks to: research a topic, do a deep dive, investigate, gather evidence, compare options, write a literature review, build a briefing, or produce a cited report.
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 reusable Jacobian capabilities from a mathematical solution corpus, rather than one agent trajectory.
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。
Suggests rollback strategies for failed deployments across different platforms and failure types. Use when deployments fail and need to be reverted, including application code rollbacks, database migration reversions, infrastructure changes, and configuration updates. Supports Docker/Docker Compose environments with step-by-step procedural guidance for safe and effective rollback execution.
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。
Identify, analyze, and manage software dependencies before deployment. Use this skill when preparing applications for deployment, resolving dependency conflicts, updating dependencies, auditing security vulnerabilities, managing package versions, or troubleshooting dependency-related issues. Supports multiple package managers (npm, pip, maven, cargo, go mod, composer) and provides actionable recommendations for dependency management.
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 packaging Docker deployments as 1Panel local app store apps, including GitHub projects, docker-compose.yml files, docker run commands, app metadata, version directories, icons, README files, and 1Panel validation.
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。
Decompose the plan into research tasks — one task per ticker × skill × mode, grouped by pillar, [P]-marked by the different-files-and-no-incomplete-deps rule, with source-refs. mode: all expands to N tasks at generation, never exists as one task (Q79).
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。