Skill UI

Automates converting recordings into structured Markdown documentation, adding metadata, diarization, summaries, and captions via Whisper/Faster-Whisper for meetings, interviews, lectures, and content analysis.

Automates converting recordings into structured Markdown documentation, adding metadata, diarization, summaries, and captions via Whisper/Faster-Whisper for meetings, interviews, lectures, and content analysis.

Design scalable AWS architectures for startups with guided workflows covering requirement gathering, architecture pattern selection, IaC template generation, cost analysis, and deployment/validation using Lambda, API Gateway, ECS, Aurora, and optimization scripts.

Design scalable AWS architectures for startups with guided workflows covering requirement gathering, architecture pattern selection, IaC template generation, cost analysis, and deployment/validation using Lambda, API Gateway, ECS, Aurora, and optimization scripts.

A comprehensive REST SDK for TypeScript that enables developers to analyze both text and images for harmful content using Azure AI services. It supports detecting various categories of harmful material (e.g., hate speech, violence, sexual content) and allows for advanced customization through creating and enforcing custom blocklists. Ideal for building robust content moderation layers in applications.

A comprehensive REST SDK for TypeScript that enables developers to analyze both text and images for harmful content using Azure AI services. It supports detecting various categories of harmful material (e.g., hate speech, violence, sexual content) and allows for advanced customization through creating and enforcing custom blocklists. Ideal for building robust content moderation layers in applications.

This SDK provides a comprehensive Python client for Azure AI Vision 4.0, enabling advanced image understanding tasks. It supports generating descriptive captions, extracting content tags, detecting objects and people with bounding boxes, performing OCR (text recognition), and suggesting smart crop regions. It is ideal for computer vision applications and detailed image content analysis.

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 for engineering teams to manage critical incidents related to Clerk authentication and SaaS platform outages. It covers full incident lifecycle procedures, including initial triage, emergency auth bypass implementation, key rotation, session recovery scripts, and post-incident root cause analysis. Use this when facing production authentication failures or security breaches.

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 production-ready coding patterns for integrating Deepgram using TypeScript and Python. This guide covers essential best practices, including implementing singleton client management, performing text-to-speech synthesis with Aura, and setting up advanced audio intelligence pipelines (e.g., summarization, topic detection, sentiment analysis). Use this when establishing robust Deepgram integration standards, refactoring existing SDK usage, or migrating to newer SDK versions.

A comprehensive set of production-ready design patterns for integrating with the Documenso SDK. It covers best practices for managing singleton clients, building typed service wrappers, robust API error handling (including status code analysis), and automatically implementing retry logic with exponential backoff. Ideal for establishing stable, scalable, and maintainable coding standards in TypeScript and Python.