3,604 件 ・ 関連度順
概要と使いどころ
Plan compelling App Store screenshot sequences that showcase your app's value. Use when preparing App Store assets, improving screenshot conversion, or drafting screenshot captions for a launch or major update.
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。
SimBu can be used to simulate bulk RNA-seq datasets with known cell type fractions. You can either use your own single-cell study for the simulation or the sfaira database. Different pre-defined simulation scenarios exist, as are options to run custom simulations. Additionally, expression values can be adapted by adding an mRNA bias, which produces more biologically relevant simulations.
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The scDblFinder package gathers various methods for the detection and handling of doublets/multiplets in single-cell sequencing data (i.e. multiple cells captured within the same droplet or reaction volume). It includes methods formerly fou
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MSA2dist calculates pairwise distances between all sequences of a DNAStringSet or a AAStringSet using a custom score matrix and conducts codon based analysis. It uses scoring matrices to be used in these pairwise distance calcualtions which can be adapted to any scoring for DNA or AA characters. E.g. by using literal distances MSA2dist calculates pairwise IUPAC distances.
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。
Expert knowledge for Azure Network Watcher development including troubleshooting, decision making, limits & quotas, security, configuration, and integrations & coding patterns. Use when configuring VNet/NSG flow logs, Traffic Analytics, packet capture, Connection Monitor migration, or VPN monitoring, and other Azure Network Watcher related development tasks. Not for Azure Monitor (use azure-monitor), Azure Virtual Network (use azure-virtual-network), Azure Networking (use azure-networking), Azure Firewall (use azure-firewall).
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。
Expert knowledge for Azure Event Hubs development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Kafka-compatible clients, Flink/Spark, geo-replication, Avro capture, or the Event Hubs emulator, and other Azure Event Hubs related development tasks. Not for Azure Service Bus (use azure-service-bus), Azure Event Grid (use azure-event-grid), Azure Notification Hubs (use azure-notification-hubs), Azure Web PubSub (use azure-web-pubsub).
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。
Deep bug analysis to break the fix-forget-repeat cycle. Analyzes root cause category, why fixes failed, prevention mechanisms, and captures knowledge into specs. Use after fixing a bug to prevent the same class of bugs.
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Captures executable contracts and coding conventions into .trellis/spec/ documents. Use when learning something valuable from debugging, implementing, or discussion that should be preserved for future sessions.
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。
Foundation skill that captures and stores core brand context — identity, audience, positioning, values, and voice. Use when the user says "set brand context", "save my brand info", "store brand details", "brand profile", "create brand context file", "update brand context", or when starting any brand project for the first time. Every other brand skill reads this file first. Always run this before beginning any brand work if the context file doesn't exist yet.
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。
Capture an architectural decision so the next session (or engineer) knows WHY. Use after any non-obvious technical choice.
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。
Pre-production story-and-character development for Higgsfield projects — the upstream layer that decides WHAT to prompt before any model runs. Use when the user wants to build a character, design a world, develop a story or premise, create a character sheet / character bible / story bible, lock a visual style or 'visual DNA', plan a multi-shot narrative with consistent characters, or says things like 'help me design a character', 'build the world', 'I need a backstory', 'make this character consistent across shots', 'develop my film/series concept', or 'I keep getting generic AI characters'. Routes the locked outputs into higgsfield-prompt + the right model. Adapted from Higgsfield's official character-design framework by @vavavinca.
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。
Repurpose one piece of affiliate content into multiple formats. Triggers on: "repurpose my content", "turn my blog into tweets", "cross-post this", "content recycling", "convert to newsletter", "make a tweet thread from this", "adapt for TikTok", "omnichannel content", "scale my content", "turn this into a LinkedIn post", "repurpose for email", "content multiplication".
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 publish social media posts for Reddit, Twitter/X, LinkedIn, Instagram, Facebook, and TikTok. Platform-specific formats, character limits, hashtag strategies, hooks, and content repurposing. Can post directly to Reddit and other platforms via API. Trigger phrases: "social media post", "tweet", "LinkedIn post", "Instagram caption", "TikTok script", "social content", "social media copy", "carousel", "thread", "social media strategy", "repurpose content", "hashtag strategy", "post to reddit", "publish on social", "post on reddit", "share on social media".
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。
Repurpose and atomize content across platforms and formats. Use when the user says "repurpose this", "turn this into", "convert blog to", "make a thread from", "content atomization", "repurpose content", "turn this article into social posts", or asks about adapting content from one format to another.
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。
Upload and fully manage YouTube videos and live events: metadata, thumbnails, captions, playlists, scheduled broadcasts, encoder streams, binding, lifecycle transitions, and cleanup.
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Step 2 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the visualization plan from outline.json — render plots and conceptual diagrams from experimental_log.md and idea.md, optionally refine via VLM critique loop, and produce context-aware captions. Runs in parallel with the literature-review-agent. TRIGGER when the orchestrator delegates Step 2 or when the user asks to "generate the figures for my paper" or "render the plots from this experiment log".
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 high-potential viral title candidates for content across WeChat public account articles, X/Twitter posts, YouTube videos, Bilibili videos, and similar content platforms. Use when the user needs headline/title ideation, batch title generation, platform-specific title adaptation, title-library reuse, title selection, title scoring, or a reusable title workflow based on universal formulas plus separated platform methods such as 公众号, X, YouTube, and B站.
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。
Download or open videos and recover platform captions, audio transcripts, keyframes, screen text, visual facts, and editing observations as a plain multimodal_transcript.md. Use for Douyin, Bilibili, YouTube, Xiaohongshu, experimental WeChat Channels links, or local video files when preparing complete source material for analysis or downstream Skill distillation.
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 working on accessibility, a11y, WCAG, ARIA, screen readers, keyboard nav, focus order, contrast, alt text, captions, reduced motion, or target sizes; not language/culture/device (see inclusive-design).
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Use when implementing crash reporting, capturing fatal/non-fatal errors, recording isolate/async exceptions, customizing reports, or uploading obfuscated symbols.
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 writing E2E/integration tests, testing native interactions like permissions or system dialogs, capturing UI regressions, or validating cross-platform behavior (Patrol 4.x).
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 generating mocks, stubbing methods, verifying interactions, capturing arguments, or choosing between mocks, fakes, and real objects (Mockito).
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 for authorized wireless security assessment including Wi-Fi capture, WPA handshake analysis, rogue AP detection research, and lab-only deauth testing.
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。
Reverse JavaScript-based custom DSL/VM interpreters, non-standard WASM-like runtimes, and risk-control engines. Use when analyzing IIFE or switch-based opcode dispatchers, extracting instruction tables, recovering bytecode semantics, capturing VM state at runtime, or reconstructing execution flow.
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。