Skill UI

This guide provides minimal working examples demonstrating the three core PostHog functionalities: event capture, user identification, and feature flag evaluation. It covers both server-side (Node.js, Python) and client-side (JavaScript) SDK usage, as well as direct API calls, making it perfect for initial integration setup, testing, and learning basic product analytics patterns.

This guide provides a comprehensive workflow for setting up a robust local development environment for PostHog integrations. It covers enabling debug mode for real-time event inspection, implementing mocking strategies for stable unit testing, and configuring integration tests using a dedicated development PostHog project. Use this when building or testing analytics tracking features with posthog-js or posthog-node to ensure fast, isolated development cycles.

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.

Blueprint skill describing the architecture, stack, folder layout, API patterns, and testing/deployment workflows used by the Zenith AI customer discovery platform clade. Use it as a reference when working on this dedicated project to understand expectations for frontend, backend, AI integration, and QA.

Guides developers through when and how to apply property-based testing across serializers, validators, normalizers, and smart contracts, highlighting properties, priorities, and workflow steps that complement existing unit testing efforts.

This skill provides guidance and patterns for generating pairwise test cases. Pairwise testing is an advanced testing technique used in software quality assurance (QA) to ensure that every combination of two input parameters is tested. It is highly effective for complex systems with multiple interacting variables, helping developers improve test coverage efficiently while minimizing the overall number of required test cases.

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.

An end-to-end workflow for building robust, production-ready Python backend APIs. This guide covers all stages, including project scaffolding, SQLAlchemy database integration, Pydantic validation, implementing JWT/OAuth2 authentication, comprehensive error handling, unit testing, and Docker deployment for modern microservices.

Provides a comprehensive pytest-focused testing strategy for Python applications, covering TDD cycles, fixtures, parametrization, coverage tools, and test infrastructure setup for reliable suites.

This comprehensive guide provides robust strategies for testing Python code using industry best practices. It covers essential techniques like pytest, fixtures, mocking, parameterization, and implementing Test-Driven Development (TDD). Use this skill when writing unit tests, setting up complex test suites, performing integration testing, or establishing continuous testing infrastructure in CI/CD pipelines.

This skill simulates the role of a quantitative analyst, providing comprehensive tools for building complex financial models, backtesting trading strategies, and analyzing market data. It covers advanced topics like portfolio optimization (Markowitz, Black-Litterman), calculating risk metrics (VaR, Sharpe ratio), and performing statistical arbitrage. Ideal for quantitative finance professionals needing rigorous data analysis, robust backtesting, and risk-adjusted performance evaluation.

Specializes in building modern, high-performance Rails 7+ web applications. Expertise includes optimizing Active Record queries (N+1 prevention), implementing partial page updates with Hotwire (Turbo Frames/Streams), handling real-time communication via Action Cable, and managing background jobs using Sidekiq. The process includes rigorous RSpec testing and database schema management.