2.2万 件 ・ 関連度順
概要と使いどころ
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the `cacheComponents` flag, work through a flood of blocking-prerender / instant validation errors, run the `cache-components-instant-false` codemod, or decide between opting routes out with `export const instant = false` and fixing them in place.
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。
Bringing up a complete ROS2 system on a robot's onboard computer: systemd services, launch file composition, ordered startup, and production monitoring. Use this skill when configuring a robot to start ROS2 nodes on boot, writing systemd unit files for ROS2 launch, composing layered launch files for full robot stacks, setting up watchdog monitoring, configuring udev rules for deterministic device naming, or debugging boot-time race conditions. Trigger whenever the user mentions robot bringup, robot startup, systemd for ROS2, ROS2 on boot, launch file composition, robot boot sequence, udev rules for cameras or serial ports, automatic restart for ROS2 nodes, network configuration for multi-machine ROS2, log rotation for robots, graceful shutdown of robot stacks, or SSH-based remote debugging. Also trigger for sourcing workspaces in systemd, ordered startup with health checks, or running ROS2 systems as long-running production services. Covers systemd on Ubuntu 22.04/24.04 with ROS2 Humble, Iron, and Jazzy.
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 comprehensive code review capability for React applications, validates component architecture, hooks usage, React 19 patterns, state management, performance optimization, accessibility compliance, and TypeScript integration. Use when reviewing React code changes, before merging pull requests, after implementing new features, or for component architecture validation. Triggers on "review React code", "React code review", "check my React components".
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 complete shadcn/ui component library patterns including installation, configuration, and implementation of accessible React components. Use when setting up shadcn/ui, installing components, building forms with React Hook Form and Zod, customizing themes with Tailwind CSS, or implementing UI patterns like buttons, dialogs, dropdowns, tables, and complex form 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。
When the user wants to set up ongoing tracking of competitor activity — pricing changes, feature launches, hiring signals, content, or public mentions. Also use when the user mentions "track competitors", "what are competitors doing", "competitor alerts", or "market watch".
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。
Migrate Databricks workloads from classic compute to serverless compute. Use when migrating notebooks, jobs, pipelines, or Scala JARs (`spark_jar_task`) from classic clusters to serverless, checking if existing code is serverless-compatible, or writing new serverless-compatible code. Provides concrete fixes for the serverless Spark Connect architecture and guides the full migration. Not for classic DBR version upgrades or cluster configuration changes within classic compute.
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。
Guides a comprehensive organisational data protection audit against key GDPR requirements including Articles 5, 24, 25, 28, 30, 32, 35, and 37. Includes 50+ control points covering principles, accountability, security, and governance. Activate when performing compliance audits, preparing for supervisory authority inspections, or assessing organisational GDPR maturity. Keywords: data protection audit, compliance audit, GDPR audit, control points, accountability.
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。
Compares PIA/DPIA methodologies: CNIL PIA tool, ICO DPIA template, NIST Privacy Framework, and ISO 29134. Provides methodology selection criteria based on regulatory jurisdiction, organisation maturity, processing complexity, and resource availability. Covers regulatory acceptance, tool features, and cross-methodology mapping. Keywords: PIA methodology, CNIL, ICO, NIST Privacy Framework, ISO 29134, DPIA comparison, assessment.
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。
Scene composition and orchestration skill for creating complex multi-part animations. **Triggers when:** - User wants to compose multi-element scenes - Request involves combining multiple visual elements - Scene requires act-based structure or transitions - User mentions "scene", "compose", "combine", "orchestrate" **Capabilities:** - Scene graph construction with acts and transitions - Multi-object coordination and timing - Camera movements and focus control - Layered animation sequences
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 first for any Jetpack Compose or Compose Multiplatform task: a new feature or screen, a change to existing code, a bug fix, a review, making code follow the kit, project or build setup, or a question. It picks the task path and the exact kit files to read. Not for Kotlin work outside a Compose or CMP app.
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。
Competitive Ad Intelligence. Analyzes competitor advertising strategies including platform identification, landing page analysis, targeting reverse-engineering, positioning gaps, creative approach evaluation, and builds a "beat the competition" strategy with a competitor ad swipe file template.
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。
Automatically complete partial code snippets while satisfying semantic constraints including variable types, invariants, pre/post-conditions, interface contracts, and expected input/output behavior. Use when users provide incomplete code with specific requirements like "complete this function that takes a list and returns sorted unique elements" or "fill in this method body that must maintain the invariant that x stays positive" or "implement this interface method with these type constraints." Produces compilable, executable code with tests and a constraint satisfaction 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。
Generate, refine, compare, and when needed validate distinctive names for startups, AI products, developer tools, protocols, open-source projects, apps, product families, local businesses, services, companies, nonprofits, and other organizations. Use when asked to name or rename a business, brand, product, venture, shop, studio, or organization; derive a name from an existing project or concept; create a company and product naming system; compare candidates; or check company, domain, package, repository, marketplace, or trademark conflicts. Default to a fast no-browse creative pass; use current validation when the user requests availability or research, or is choosing a final name. Do not claim legal clearance, purchase domains, or present stale or unverified availability as fact.
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。
Think and work like an expert Computer Scientist. Use when a task calls for Computer Scientist judgment. Reasons from computational models, abstraction contracts, invariants, and measurable complexity through CLRS-grade algorithm analysis, impossibility results (FLP, CAP, NP-hardness), property-based and chaos testing, and formal tools (TLA+, Coq, Z3) while treating partial failure, race conditions, label leakage, and abstraction leaks like GC pauses and clock skew as first-class failure modes.
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。
Business model classification, business model analysis, structural analysis of how a company makes money, product offering decomposition, distribution channel analysis, customer segment analysis, revenue model identification, market sizing TAM SAM SOM, competitive positioning, business unit performance, management team & leadership analysis, what does the company sell, how does the company go to market, business model type platform service product, channel mix direct vs indirect, revenue concentration risk, CEO CFO executive backgrounds and changes
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。
Peer benchmarking, multi-ticker financial comparison, growth value matrix, composite z-score ranking, industry peer comparison, competitive benchmarking, sector relative performance, peer group analysis, industry leader comparison, financial ratio benchmarking
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。
Provider-independent VFX compositing direction for generated video, ads, trailers, product films, social clips, explainers, mixed-source edits, and image/video composites. Use when an agent must plan, brief, generate, integrate, repair, or quality-check visual effects composites involving plates, alpha/mattes, keying, roto, tracking, stabilization, matchmove, lighting/color integration, grain/noise/sharpness, shadows/reflections/contact, depth/atmosphere, AI-generated elements, clean plates, editor/colorist handoff, rights/safety, or compositing QA.
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。
Enrich any company with comprehensive firmographic data including industry, size, revenue, funding, tech stack, beneficial ownership, and regulatory status. Combines multiple data sources for complete B2B company intelligence and due diligence.
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。
Monitor competitor websites, content changes, social activity, and market positioning through SandBase. Use when asked for competitive intelligence, competitor tracking, market positioning research, or competitive content monitoring.
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。
Detect A/B compartments from Hi-C data using cooltools and eigenvector decomposition. Identify active (A) and inactive (B) chromatin compartments from contact matrices. Use when identifying A/B compartments from Hi-C 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。
Visualizes ChIP-seq data using deepTools (computeMatrix, plotHeatmap, plotProfile, bamCoverage, bamCompare), pyGenomeTracks (modern INI-driven track plots), Gviz (R browser-style), EnrichedHeatmap (ComplexHeatmap-based), ChIPseeker tag heatmaps, and IGV batch screenshots. Handles bigWig normalization choices (CPM, BPM, RPGC, spike-in scaled), bamCompare operations (log2 ratio, subtract, SES), k-means clustering of heatmaps for biological subgrouping, and spike-in-scaled tracks for global-shift experiments. Use when generating publication-quality ChIP-seq signal heatmaps, profile plots, genome-browser tracks, or comparing samples visually.
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 authoring reusable, idempotent MATLAB scripts that build System Composer architecture models via the architecture-modeling API — `systemcomposer.createModel`, `addComponent`, `addPort`, `setInterface`, `connect(srcPort, dstPort)`, interface dictionaries (.sldd) with `addInterface`/`addElement`, profiles/stereotypes with `Profile.createProfile` and `addStereotype`, or `systemcomposer.allocation.createAllocationSet`. Also trigger when debugging these APIs (connections that don't appear, interfaces that don't resolve, profile save errors, `createAllocationSet` signature-mismatch errors). Do NOT trigger for ad-hoc structural edits to an already-built model (adding one SubSystem, rewiring a port) — use `building-simulink-models` with `model_edit` for that.
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。
Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI. Provides project context, component docs, and usage examples. Applies when working with shadcn/ui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for "shadcn init", "create an app with --preset", or "switch to --preset".
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。
Side-by-Side Property Comparison — takes two addresses and compares across price, specs, rental income, neighborhood, and investment potential with a winner per category and overall recommendation
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。