Skill UI

This SDK provides comprehensive Python support for Azure Data Lake Storage Gen2. It enables developers to interact with hierarchical file systems, performing essential big data operations such as creating, listing, uploading, downloading, and managing metadata for files and directories. Ideal for building data analytics pipelines and cloud-based data processing workflows.

A comprehensive skill for creating, editing, and automating complex spreadsheet workflows using LibreOffice Calc. This includes generating new ODS files, performing format conversions (XLSX, CSV, PDF, etc.), executing advanced formulas, and automating data processing through Python scripting (UNO, ezodf) or command-line interfaces. Ideal for data analysis, reporting, and batch processing tasks.

A comprehensive guide to essential Bash and Linux command patterns for macOS and Linux systems. Covers fundamental scripting concepts, including command chaining (&&, ||), file operations (find, grep, sed, awk), process management, text processing, environment variable handling, and network utilities (curl). Ideal for automating system tasks and improving command-line efficiency.

A comprehensive guide to optimizing costs associated with AI code review tools like CodeRabbit. Learn strategies for right-sizing seat allocation, scoping services to high-value repositories, and implementing granular file filters to minimize unnecessary AI processing and billing overhead. Essential for managing SaaS spend in a DevOps environment.

Implements a robust caching strategy by using the SHA-256 hash of file content as the primary key, instead of the file path. This pattern is essential for high-cost file processing pipelines (like OCR, PDF parsing) because it ensures cache hits survive file renaming or moving, while still automatically invalidating entries when the content changes. It adheres to the Single Responsibility Principle (SRP) by isolating caching logic into a service layer wrapper.

A comprehensive workflow for production-grade, pre-recorded Speech-to-Text (STT) transcription using the Deepgram API. This skill supports transcribing audio from URLs or local files, offering advanced features such as speaker diarization, automatic summaries, sentiment analysis, and topic detection. It also includes robust batch processing methods for handling large datasets.

Provides reference architectures for building high-scale, reliable transcription systems using Deepgram. It covers four main patterns: synchronous REST for short files, async queues (BullMQ) for batch processing, WebSocket for real-time streaming, and a hybrid router for mixed workloads. Use this when designing production-grade audio processing pipelines.

This skill provides guidance and patterns for generating structured JSON files that define complex workflow pipelines. It is essential for chaining multiple distinct AI models together, enabling multi-step, automated data processing. Use this when a single task requires a sequence of interconnected AI operations or services.

This skill provides comprehensive automation for content workflows using the Gamma API. It allows users to generate multiple variations from a single template, support batch processing, and specify export formats (PDF, PPTX, PNG). Furthermore, it handles the retrieval of final exported files and configures detailed sharing permissions, making it ideal for structured, large-scale content distribution.

This skill guides developers through setting up and processing Lokalise webhooks for real-time content synchronization. It covers the API integration steps to register webhook endpoints, handling various translation lifecycle events (key creation, translation updates, file imports), and implementing secure payload verification using webhook secrets. It demonstrates building robust, asynchronous event handlers in Node.js/Express, perfect for automating workflows based on content changes in a SaaS environment.

A comprehensive guide for optimizing Obsidian plugin performance, especially when dealing with large knowledge vaults (10,000+ files). Learn advanced techniques such as profiling bottlenecks with DevTools, implementing lazy initialization to speed up startup, processing files in manageable batches with UI yielding, and utilizing LRU caches for bounded memory management. Essential for creating stable, high-performance plugins.

This skill provides advanced patterns for handling high-volume Obsidian file operations, such as debouncing keystrokes, batching file reads, and throttling UI updates. It addresses single-threaded performance bottlenecks, ensuring plugins remain responsive and prevent UI freezes during bulk processing or rapid user interactions.