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概要と使いどころ
Preprocesses cell-free DNA sequencing data including adapter trimming, alignment optimized for short fragments, and UMI-aware duplicate removal using fgbio. Applies cfDNA-specific quality thresholds and fragment length filtering. Use when processing plasma cfDNA sequencing data before downstream analysis.
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Deploy an event-driven workflow that routes S3 uploads to either Lambda or Fargate via Step Functions based on file size. Uses EventBridge to trigger a Step Functions state machine when objects are uploaded to S3. Small files are processed by Lambda, large files by a Fargate task. Includes VPC, ECR repository, ECS cluster, and scoped IAM roles. Trigger keywords: Step Functions, Fargate, Lambda, S3 event, EventBridge, ECS, ECR, file processing, workflow orchestration, serverless.
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Implement event-driven patterns with Claude API: streaming SSE events, Message Batches callbacks, and async processing architectures. Use when building real-time Claude integrations or processing batch results. Trigger with phrases like "anthropic events", "claude streaming events", "anthropic async processing", "claude batch callbacks".
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macOS process injection playbook. Use when you need to inject code into running or launching macOS processes via dylib hijacking, DYLD environment variables, XPC exploitation, Mach port manipulation, or Electron/Chromium abuse.
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Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
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Designs, documents, and fixes operational processes — mapping the current state, finding where work actually stalls, redesigning the flow, and building controls that hold. Use this when the same failure keeps recurring, when a handoff between teams is unreliable, when onboarding a repeated task, when work takes far longer than the work itself, or when deciding whether to automate, standardize, or eliminate a process.
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Generates complete conventional non-oncology bioinformatics research designs from a user-provided disease context, process-related gene family or biological theme, and validation direction. Use when a study centers on multi-dataset bulk transcriptome integration, DEG analysis, process-gene intersection, enrichment analysis, GSEA, PPI hub-gene prioritization, TF/miRNA regulatory networks, ROC-based biomarker evaluation, and immune infiltration analysis. Covers five study patterns (process-DEG discovery, enrichment/GSEA interpretation, hub-gene prioritization, regulatory-network and immune interpretation, multi-layer public validation) and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.
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。
Process videos by removing segments and concatenating remaining parts. Use when you need to remove detected pauses/openings from videos, create highlight reels, or batch process segment removals using ffmpeg filter_complex.
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Atlas turns your STATED NEED into a real systems atlas by SCANNING your actual sources (Azure via `az`, git repos, local dirs) and process/data mining them, THEN enriching against the Atlas knowledge graph. Use this skill when asked to inventory/map your real systems, scan your cloud + repos + directories, mine the real processes or data they contain, or collect their real constraints/gotchas. (atlas, scan my systems, inventory our azure account, map my repos, real systems atlas, process mining, data mining, collect nuances, system discovery)
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Troubleshoot and resolve issues with Azure Messaging SDKs for Event Hubs and Service Bus. Covers connection failures, authentication errors, message processing issues, and SDK configuration problems. WHEN: event hub SDK error, service bus SDK issue, messaging connection failure, AMQP error, event processor host issue, message lock lost, message lock expired, lock renewal, lock renewal batch, send timeout, receiver disconnected, SDK troubleshooting, azure messaging SDK, event hub consumer, service bus queue issue, topic subscription error, enable logging event hub, service bus logging, eventhub python, servicebus java, eventhub javascript, servicebus dotnet, event hub checkpoint, event hub not receiving messages, service bus dead letter, batch processing lock, session lock expired, idle timeout, connection inactive, link detach, slow reconnect, session error, duplicate events, offset reset, receive batch.
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Run a decision asynchronously — the memo, the silent-read window, the comment protocol, and the deadline that makes it land without a meeting. Use when asked to decide something async, replace a decision meeting with a document, run an Amazon-style written decision process, or when a decision keeps stalling in comment threads. Produces the decision memo plus the process wrapper: reader roles, response windows, comment-resolution rules, and the tie-breaker. For the document structure alone use decision-memo; this skill runs the process around 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。
Request a reasonable accommodation at work or in education — frame it around the barrier and the adjustment (not your diagnosis), cite the right process, and navigate the back-and-forth constructively. Use when someone says 'I need a workplace accommodation', 'request reasonable adjustments', 'ADA/Equality Act accommodation', or 'how do I ask for accommodations for my disability/condition'. Produces the request letter, a barriers-and-adjustments map, disclosure guidance, and a plan for the interactive process. Not legal advice — routes to the formal process and to advocacy where needed.
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Design an AI-assisted workflow for a recurring task — which steps to hand to AI, which to keep human, and how they connect — so you get leverage without losing quality or control. Use when asked how do I use AI for [process], automate this with AI, design an AI workflow, or where does AI fit in my process. Produces a map of the task's steps split into AI-does / human-does / human-checks, the right tool/prompt for each AI step, the hand-offs and review points, the failure modes to guard against, and a start-small rollout — turning a manual process into a reliable AI-assisted one that keeps you in control.
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Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.
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Use when understanding and navigating Administrative Science Quarterly's (ASQ) developmental, multi-round review process — decision types, reviewer/editor roles, and what each stage expects. Explains the process; it does not draft the response letter (see asq-rebuttal).
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Use when you need to understand or set expectations for the Academy of Management Journal (AMJ) editorial and peer-review process — desk review, the developmental multi-round R&R culture, and reading a decision letter. Explains the process and how to read decisions; it does not draft the response letter (amj-rebuttal).
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 planning around the two-step proposal→invited-review process of the Academy of Management Annals (Annals) — the twice-yearly proposal cadence, double-blind proposal review, the editor-only full-review development, and timelines. Explains the process; it does not write the proposal (amann-proposal-framing) or run the portal preflight (amann-submission).
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。
Decides how to preprocess plasma cfDNA sequencing data so the recoverable signal survives - library-prep-aware fragment expectations (dsDNA vs ssDNA/adaptase prep), UMI/duplex consensus with fgbio (ExtractUmisFromBam, GroupReadsByUmi --strategy paired for duplex, CallMolecularConsensusReads vs CallDuplexConsensusReads, FilterConsensusReads min-reads "total s1 s2"), the align->group->consensus->RE-align ordering, and the cfDNA dedup trap where naive coordinate dedup collapses nucleosome-coincident independent molecules. Covers when single-strand consensus suffices vs when duplex is mandatory, the singleton/sensitivity tax at low input, and reading the insert-size histogram as a pre-analytical QC instrument. Use when processing plasma cfDNA reads before fragmentomics, ctDNA mutation calling, or tumor-fraction estimation.
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。
Schedule and execute background work on iOS using BGTaskScheduler. Use when registering BGAppRefreshTask for short background fetches, BGProcessingTask for long-running maintenance, BGContinuedProcessingTask (iOS 26+) for foreground-started work that continues in background, background URLSession downloads, or background push notifications. Covers Info.plist configuration, expiration handling, task completion, and debugging with simulated launches.
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Load this first for any task involving images, pictures, photos, scans, frames, volumes, or visual data — including reading, writing, filtering, enhancing, denoising, sharpening, deblurring, thresholding, segmenting, masking, detecting, finding or counting objects, removing backgrounds, measuring, comparing, registering, stitching, aligning, cropping, resizing, transforming, or analyzing. Use for image I/O (TIFF, PNG, JPEG, RAW, HDR), histograms, edge detection, color processing, morphology, geometric transforms, deep learning for images, quality assessment, and 3-D volume processing. Also triggers when users describe image problems (dark, noisy, blurry, low contrast, uneven lighting, hazy, color cast) or data exploration tasks (folder of images, characterize data, understand format). Handles microscopy (cells, particles) and general scientific imaging. Routes to sibling skills for medical imaging (DICOM, NIfTI), hyperspectral data, and visual inspection.
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Process images for web development — resize, crop, trim whitespace, convert formats (PNG/WebP/JPG), optimise file size, generate thumbnails, create OG card images. Uses Pillow (Python) — no ImageMagick needed. Trigger with 'resize image', 'convert to webp', 'trim logo', 'optimise images', 'make thumbnail', 'create OG image', 'crop whitespace', 'process image', or 'image too large'.
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 ISO 27701 Privacy Information Management System (PIMS) compliance advisor. Use this skill whenever a user asks about ISO/IEC 27701:2025, ISO/IEC 27701:2019, privacy information management, PIMS certification, PII controller or processor obligations, privacy risk assessment, Statement of Applicability for privacy, privacy by design, data subject rights, DPIA, records of processing activities, transitioning from ISO 27701:2019, GDPR alignment with ISO 27701, or any privacy management system topic. Also trigger for questions about Annex A.1 (controller controls), A.2 (processor controls), A.3 (shared security controls), or implementing a standalone PIMS without ISO 27001. When in doubt, use this skill — it covers the full ISO 27701 lifecycle from gap assessment through certification.
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。
Operations leadership advisor on business operations, process optimization, and scaling infrastructure. Use when designing operational processes, planning headcount capacity, optimizing vendors, or scaling operations.
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 ISO 27701 Privacy Information Management System (PIMS) compliance advisor. Use this skill whenever a user asks about ISO/IEC 27701:2025, ISO/IEC 27701:2019, privacy information management, PIMS certification, PII controller or processor obligations, privacy risk assessment, Statement of Applicability for privacy, privacy by design, data subject rights, DPIA, records of processing activities, transitioning from ISO 27701:2019, GDPR alignment with ISO 27701, or any privacy management system topic. Also trigger for questions about Annex A.1 (controller controls), A.2 (processor controls), A.3 (shared security controls), or implementing a standalone PIMS without ISO 27001. When in doubt, use this skill — it covers the full ISO 27701 lifecycle from gap assessment through certification.
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。