Skill UI

A comprehensive guide to implementing production-ready patterns for PostHog analytics integration. This includes establishing singleton clients for both server-side (Python/Node) and client-side environments. It provides type-safe event capture utilities, React hooks for handling feature flags (including variants), and the full Next.js App Router setup for robust pageview tracking. Patterns are available for both TypeScript/JavaScript and Python environments.

A comprehensive guide for safely upgrading PostHog SDKs (for JavaScript and Node.js). This resource details critical breaking changes across major versions, such as the explicit requirement for `sendFeatureFlags` in v5.x and the new structured autocapture API for PostHog.js. It provides a structured, step-by-step procedure covering version auditing, code modification, testing, staging validation, and rollback plan.

Guides SaaS teams through value-based pricing, tier design, research techniques (Van Westendorp, MaxDiff) and pricing-page best practices to capture customer willingness to pay and support monetization decisions.

This comprehensive skill helps establish and maintain a foundational 'Product Marketing Context' document. It serves as a single source of truth, capturing critical details like Ideal Customer Profile (ICP), core pain points, competitive landscape, and brand voice. Use this skill at the start of any new project to ensure consistent, deep, and accurate marketing messaging across all downstream tasks.

This skill provides comprehensive methodologies for capturing, analyzing, and documenting network protocols. It is crucial for security researchers, developers ensuring interoperability, and engineers debugging complex network communications by understanding the underlying data exchange mechanisms.

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.

Ray Data offers scalable distributed data processing for ML workloads, streaming across CPU/GPU clusters and integrating with PyTorch, TensorFlow, and Ray Train. Use it for batch inference, ETL, and multi-modal preprocessing from a laptop up to hundreds of nodes.

Ray Train orchestrates distributed PyTorch, TensorFlow, and HuggingFace workloads from laptops to clusters, automating GPU placement, fault tolerance, checkpointing, and hyperparameter sweeps so teams can scale massive model training with minimal code changes.

This guide provides comprehensive best practices for creating high-quality videos using Remotion within a React environment. It covers advanced techniques for dynamic content generation, including integrating 3D models (Three.js), managing diverse assets like audio, video, and fonts, implementing complex animations, data visualization, and generating precise captions. Use this skill when developing professional, robust video generation workflows in React.

A comprehensive guide for migrating existing applications from platforms like Heroku, Railway, Vercel, and local development environments to Replit. It covers critical steps such as converting configuration files (Procfile to .replit), adapting to Replit's Nix-based system, and performing database migrations (PostgreSQL, MongoDB). Essential for developers upgrading or moving their deployment stack.

This skill provides a comprehensive guide for setting up and managing webhook endpoints for Retell AI. It allows developers to capture and process crucial call lifecycle events—such as call start, end, and analysis—as well as handle function calls triggered during live conversations. Use this when building sophisticated voice agents or call automation systems that require real-time backend interaction with Retell AI.

Automates Seat Geek operations via Rube MCP and Composio’s toolkit, guiding you through tool discovery, connection checks, and schema-compliant multi-tool execution while adapting to evolving APIs.