Skill UI

A comprehensive guide for building applications that interact with Azure Blob Storage using the Azure SDK for Java. Covers essential patterns including client initialization (via connection string or credentials), uploading/downloading data from files or streams, listing blobs, and managing containers. Ideal for developers building scalable cloud data storage solutions.

This SDK provides a comprehensive Python interface for interacting with Azure Blob Storage, Microsoft's scalable object storage service. It enables users to perform core object storage operations, including uploading, downloading, listing, deleting blobs, managing containers, and setting custom metadata. The library supports both synchronous and asynchronous workflows, making it ideal for building robust data pipelines, data lakes, or cloud-native applications that require reliable, scalable file storage.

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.

This SDK provides comprehensive Python support for managing Azure File Shares, which function as SMB file shares in the cloud. It allows users to perform core operations including creating, listing, and deleting shares, managing nested directories, uploading, downloading, and copying files, and utilizing advanced features like snapshots and partial range operations. Ideal for cloud-native development and lift-and-shift migrations.

A comprehensive JavaScript/TypeScript SDK for interacting with Azure File Shares. This library facilitates full lifecycle management of SMB file shares, including creating, listing, and deleting shares, managing quotas, and performing robust file and directory operations (uploading via stream, buffer, or file paths; downloading streamed content). Ideal for modern cloud-native applications requiring persistent file storage.

Automates Dropbox file, folder, sharing, upload/download, search and metadata workflows via the Rube MCP (Composio) toolkit while always querying the latest schemas before invoking storage tools.

Provides expert guidance on secure and performant file upload mechanisms for cloud environments. Covers best practices for using services like AWS S3 and Cloudflare R2, including implementing presigned URLs, handling large files via streaming, and optimizing images. Crucially emphasizes critical security measures such as validating file types using magic bytes, enforcing size limits, and preventing path traversal attacks.

This guide provides a comprehensive, multi-step technical process for migrating historical meeting recordings and data into the Fireflies.ai ecosystem. It covers various scenarios, including batch uploads from public URLs, importing authenticated files (S3/GCS), direct file uploads, and tracking progress via webhooks, ensuring a robust and validated transition from competitor platforms.

A comprehensive guide to integrating Lokalise into Continuous Integration/Continuous Deployment (CI/CD) workflows using GitHub Actions. This setup automates the entire translation lifecycle: uploading source strings on code pushes, downloading the latest translations during builds, and running PR checks to ensure translation coverage across all required locales. It eliminates manual file management, keeping code, translations, and CI pipelines perfectly synchronized.

This comprehensive workflow automates the core source-to-Lokalise process. Users can upload source translation files (JSON, XLIFF, PO, etc.), programmatically create new keys from code scans or CMS exports, update existing keys, and manage release tags. It is designed for CI/CD pipelines and bulk content synchronization.

A comprehensive deep dive guide for migrating translation memory (TM) and localization content from competing Translation Management Systems (TMS) like Crowdin, Phrase, or POEditor into Lokalise. This process involves exporting data from the source platform, transforming key variables and file structures to match Lokalise conventions, and finally performing a bulk API upload to establish a new, centralized localization repository. Perfect for re-platforming or migrating existing translation pipelines.

Automate OneDrive file management tasks through Composio's Rube MCP toolkit, handling uploads, downloads, search, sharing links, permissions, and folder navigation via documented tool sequences once the MCP connection is active.