Skill UI

This skill guides you through integrating PostHog's Customer Data Platform (CDP) features. It covers setting up webhooks to trigger real-time actions (e.g., syncing to CRM, sending notifications) when specific user events occur. Furthermore, it demonstrates how to query event data using the Events API and perform complex funnel analysis using HogQL, allowing for deep, custom insights into user behavior.

This skill demonstrates the multi-model pattern for creating robust and clean API contracts using Pydantic. It guides the creation of separate models for creation requests (Create), updates (Update), responses (Response), and database documents (InDB), ensuring type safety and clear data validation for Python backends. It also covers best practices like handling camelCase aliases and optional fields.

This skill guides developers through modernizing React applications. It covers migrating from class components to functional components using hooks, upgrading React versions, adopting concurrent features (like Suspense), and applying automated refactoring techniques using codemods. It is essential for maintaining high-performance, modern React codebases and integrating TypeScript.

A comprehensive guide to modern React state management patterns. It covers various state types—including local, global, server, and form state—and demonstrates best practices using industry-leading libraries like Redux Toolkit, Zustand, Jotai, and React Query. Use this when building complex, scalable React applications and needing to select the optimal state solution.

This skill guides users through building a minimal yet comprehensive working application on the Replit platform. It demonstrates how to integrate and use core platform services such as the built-in Key-Value Database, Object Storage for file handling, user Authentication, and standard web frameworks (Express/Flask). Use this guide when starting a new Replit project or when learning the foundational infrastructure services provided by the platform.

This workflow guides users through building advanced AI voice agents using the Retell AI SDK. It demonstrates how to implement complex call flows, integrate function calling for tasks like booking appointments, and configure voice behavior for professional telephony applications.

This comprehensive guide demonstrates how to build and test a voice agent using the Retell AI SDK in TypeScript. It walks through configuring the underlying LLM with a custom persona, creating the voice agent instance, and finally initiating both outbound phone calls and web calls through the API. This is essential for integrating AI-powered voice communication into customer service platforms, call centers, or telephony automation systems.

Guides sales engineers through RFP/RFI analysis, competitive feature matrices, POC planning, demo prep, and proposal delivery using Python tooling and checkpoints to ensure coverage, differentiators, and win/loss insights.

Basic Text Processor provides word/character statistics, simple text transformations, batch file handling, and dual JSON or human-readable outputs to demonstrate a CLAUDE skill template.

This skill provides a comprehensive walkthrough for setting up and testing Sentry error monitoring using both Node.js and Python SDKs. It demonstrates how to capture various event types, including simple messages and full exceptions, and crucially, how to enrich these events with user context, searchable tags, and detailed breadcrumbs. This is essential for verifying robust error logging and monitoring in a production environment.

This skill guides the setup of distributed tracing and performance monitoring using Sentry. It covers configuring the SDK (e.g., setting tracesSampleRate) to capture latency, identify performance bottlenecks, and trace requests across the entire application stack. It demonstrates how to create manual spans for business logic and utilizes profiling for deeper performance insights, ensuring comprehensive application observability.

This skill guides developers through major Sentry SDK version upgrades (e.g., v7 to v8, Python v1 to v2). It helps detect deprecated APIs, runs automated codemods (like @sentry/migr8), and applies manual fixes for breaking changes, ensuring a smooth transition while maintaining robust error tracking and observability.