Skill UI

Checks website, GitHub, and local docs to identify messaging inconsistencies and captures version, feature, terminology, and contact differences in a read-only discrepancy report whenever a consistency check is requested.

Automates adapting pretrained models via transfer learning by analyzing requirements, generating PyTorch or TensorFlow fine-tuning code, validating data, tracking KPIs, and saving artifacts so you can quickly reuse existing models for new datasets and tasks.

Automatically generate comprehensive, developer-friendly API documentation directly from your codebase. This skill captures details like endpoints, parameters, request/response schemas, authentication methods, and provides runnable code examples (cURL, Python, JS). It is perfect for documenting REST, GraphQL, and WebSocket APIs, and generating OpenAPI/Swagger specifications.

Provides structured ADR patterns, templates, and practices for capturing significant architectural decisions, rationale, tradeoffs, and lifecycle status to onboard teams and review historical choices.

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.

This SDK provides a comprehensive Python client library for interacting with Azure AI Speech-to-Text services. It supports both real-time streaming transcription and robust batch processing of audio files. Users can leverage advanced features such as speaker diarization (identifying multiple speakers) and capturing precise timestamps, making it invaluable for automated meeting minute generation, podcast content processing, and live captioning solutions.

This SDK provides a comprehensive Python client library for interacting with Azure AI Speech-to-Text services. It supports both real-time streaming transcription and robust batch processing of audio files. Users can leverage advanced features such as speaker diarization (identifying multiple speakers) and capturing precise timestamps, making it invaluable for automated meeting minute generation, podcast content processing, and live captioning solutions.

This SDK provides Java developers with access to advanced image analysis features from Azure AI Vision. It allows applications to perform various visual tasks, including OCR text extraction, generating detailed image captions, detecting specific objects with bounding boxes, recognizing content tags, and performing smart cropping. Use it when building applications that require deep visual understanding of images.

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.

Automates change-data-capture pipeline planning by guiding developers through ETL, orchestration, and streaming best practices, then generating validated configs and code when “cdc pipeline creator” is requested.

This skill defines structured behavioral frameworks (e.g., Brainstorm, Implement, Debug, Review, Teach, Ship) to guide the AI's output and approach based on the specific task phase. It optimizes performance by ensuring the AI adopts the correct mindset and output format—from initial ideation to final deployment—guaranteeing systematic, high-quality results across the entire development lifecycle.