Skill UI

A workflow for orchestrating Pushover operations through Composio’s Rube MCP connectors, covering tool discovery, connection validation, schema-aware execution, and recommended API calls for reliable automation.

Automates creation and validation of PWA manifest files for frontend projects, guiding developers through best practices and generating production-ready code snippets and configs for React, Vue, CSS, and modern web ecosystems.

This skill auto-activates when someone mentions pytest test generator, offering guided test automation workflows, producing ready-to-use code/configuration, and validating outputs for unit, integration, and mocking scenarios.

This skill acts as an expert architect to generate complete, production-ready Python project structures. It supports various modern architectures, including FastAPI, Django (full-stack), standalone libraries, and CLI tools. It ensures adherence to best practices, includes dependency management (uv, pip), type hinting, and comprehensive testing skeletons.

Guides adding PyTorch FSDP2’s fully_shard integration to training loops, covering correct distributed init, bottom-up sharding, mixed precision/offload policies, DTensor-aware optimizers, and distributed checkpointing so oversized models or DeviceMesh sharding goals work reliably.

High-level PyTorch Lightning streamlines training loops with automatic distributed support (DDP/FSDP/DeepSpeed), callbacks, checkpointing, logging, and device management so you can scale from a laptop to multi-node clusters without boilerplate.

Automates PyTorch training workflows by guiding data preparation, model configuration, hyperparameter tuning, and experiment tracking while following industry best practices for production readiness.

Pyvene is a declarative framework designed for performing causal interventions on PyTorch neural networks. It allows researchers to conduct advanced experiments such as activation patching, causal tracing (ROME-style), and interchange intervention training (IIT). Use this library when you need to test causal hypotheses about model behavior, deeply interpret model components, or ensure reproducibility in advanced AI research.

Qdrant is a high-performance, Rust-powered vector database designed for production-grade RAG (Retrieval-Augmented Generation) and semantic search applications. It provides fast nearest neighbor search, supports complex hybrid search using metadata filtering, and offers horizontal scalability through sharding and replication. Ideal for building real-time recommendation systems and enterprise-level knowledge retrieval.

This comprehensive guide provides expertise in conducting ISO 13485 internal audits for medical device Quality Management Systems (QMS). It covers the full audit lifecycle, including risk-based planning, systematic evidence collection, classifying nonconformities (Major/Minor), and managing CAPA verification to ensure regulatory compliance and continuous improvement.

This guide defines the role and responsibilities of a Senior Quality Manager Responsible Person (QMR) for highly regulated MedTech and HealthTech environments. It covers essential functions under ISO 13485, including leading management reviews, establishing quality objectives, monitoring performance KPIs, and maintaining strict regulatory compliance oversight. Use this resource when developing a Quality Management System (QMS) or managing regulatory accountability.

Implements and maintains ISO 13485 QMS for medical device organizations, covering gap analysis, documentation control, internal audits, supplier qualification, and CAPA tracking to keep regulatory programs audit-ready.