1.5K skills · sorted by relevance
Run batch processing, scientific simulations, and machine learning training on Google Kubernetes Engine. Configure parallel jobs, queues that manage resource access, and distributed computation, with guidance on scaling idle capacity down and recovering from interruptions.
Deploy and manage applications on Cloud Run using source code or container images. Choose services for web requests, jobs for tasks that finish, or worker pools for continuous background processing, with guidance on execution settings and deployment failures.
Receive live Lark/Feishu updates for messages, approvals, tasks, meetings, and more. Stream them as NDJSON, one JSON record per line, with filtering and time or event limits for bots and automated event processing.
Turn recorded audio and video into text or timestamped subtitles with Whisper. This skill covers transcription across 99 languages, language detection, translation into English, batch processing, and model selection for available computing resources.
Develop Salesforce workflows, interface components, and integrations using Apex and Lightning Web Components. The skill guides database queries, bulk processing, platform resource limits, testing, and deployment through Salesforce DX.
Triage proposed personal data uses to determine whether they can proceed, need a privacy impact assessment, require a legally mandated assessment, or must stop. Results explain policy conflicts, applicable triggers, and conditions to address before proceeding.
Prepare an internal Privacy Impact Assessment, a review of how a feature uses personal data. Check whether assessment is needed, examine legal grounds and policy commitments, and document specific risks, required actions, and owners in the team’s format.
Learn Apache Beam's core concepts through Java and Python examples. Understand distributed datasets, processing steps, pipeline execution, and time windows, with guidance on aggregation, late data, error handling, and sharing processing steps across languages.
Batch retouch portrait photos with Adobe tools, correcting alignment and tone and adding optional presets, background blur, or cropping. Review a sample before processing the full set, then receive previews and download links.
Make 3D canvas output sharper on Retina and other high-density displays. Coordinate rendering and post-processing resolution, preserve pointer accuracy, and verify fixed 200% rendering or automatic scaling with measured performance and explicit fallbacks.
Write JavaScript for n8n Code nodes to aggregate, filter, and transform workflow data. Guidance covers data access, output formats, execution modes, common errors, and performance choices when processing large numbers of records.
Build Python machine learning workflows for classification, numerical prediction, and grouping similar records. Use scikit-learn guidance and examples to prepare data, compare algorithms, tune model settings, and evaluate results with repeatable processing steps.
Write MATLAB or GNU Octave scripts for matrix calculations, data analysis, signal processing, and scientific plots. The skill also helps explain syntax and functions, convert code between MATLAB and Python, and run scripts when an interpreter is installed.
⚠️ CRITICAL USER EXPERIENCE-BASED SKILL - ALWAYS CONSULT BEFORE DATA PREPROCESSING ⚠️ Prevents catastrophic errors (88.9% error rate in V1.0 case study) through multi-level feature analysis, data leakage detection, and semantic validation. MANDATORY for: data preprocessing, feature engineering, standardization, normalization, interpolation, missing value handling, feature selection, or ANY data transformation task. Covers grouped time-series, cross-sectional, panel data. Detects: time travel leakage, causal inversion, ID misuse, semantic-numeric fallacies, distribution blindness. User's hard-won lessons from real project failures.
The English summary is being prepared. Showing the original description.
Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), vector and raster data operations, spatial statistics, point cloud processing, network analysis, and 7 programming languages (Python, R, Julia, JavaScript, C++, Java, Go) with 500+ code examples. Use for remote sensing workflows, GIS analysis, spatial ML, Earth observation data processing, terrain analysis, hydrological modeling, marine spatial analysis, atmospheric science, and any geospatial computation task.
The English summary is being prepared. Showing the original description.
This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.
The English summary is being prepared. Showing the original description.
XCMS3 workflow for LC-MS/MS metabolomics preprocessing. Covers peak detection, retention time alignment, correspondence (grouping), and gap filling. Use when processing raw LC-MS data into a feature table for untargeted metabolomics.
The English summary is being prepared. Showing the original description.
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".
The English summary is being prepared. Showing the original description.
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.
The English summary is being prepared. Showing the original description.
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.
The English summary is being prepared. Showing the original description.
Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.
The English summary is being prepared. Showing the original description.
Generates background processing infrastructure with BGTaskScheduler, background refresh, background downloads, and silent push handling. Use when user needs background tasks, periodic refresh, background URLSession downloads, or silent push notification processing.
The English summary is being prepared. Showing the original description.
Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, automation scripts. Triggers: python, execute code, run script, web scraping, data analysis, image processing, video editing, 3D models, automation, pandas, matplotlib
The English summary is being prepared. Showing the original description.
Production-ready PDF processing with forms, tables, OCR, validation, and batch operations. Use when working with complex PDF workflows in production environments, processing large volumes of PDFs, or requiring robust error handling and validation.
The English summary is being prepared. Showing the original description.