Skill UI

Guides email marketing pros through building multi-step sequences—welcome, nurture, onboarding, re-engagement, and lifecycle flows—emphasizing clear goals, timing, subject/preview best practices, and copy structure to nurture relationships and drive conversions.

Guides engineers through initializing MCUs, crafting RTOS-aware drivers, and tuning power/timing for STM32, ESP32, and bare-metal targets; covers constraint analysis, interrupt safety, resource tracking, and validation with static analysis and real-time debugging.

A comprehensive guide for selecting and optimizing embedding models for advanced vector search and retrieval-augmented generation (RAG) applications. This guide covers model comparison, chunking strategies, dimension reduction techniques, and provides runnable Python templates for both OpenAI and local Sentence Transformer implementations.

A comprehensive guide for building robust, event-driven APIs using Webhooks, Server-Sent Events (SSE), and message brokers (e.g., Kafka, RabbitMQ). This skill covers advanced patterns like the transactional outbox pattern, implementing event schemas, managing webhooks with retry logic, and establishing real-time streaming endpoints for asynchronous microservices communication. Ideal for architecting complex, scalable, and resilient systems.

Feature Engineering Toolkit automates creating, selecting, and transforming dataset features to improve machine learning models; use it whenever you need new interactions, automatic selection, scaling, or encoding to boost accuracy and interpretability.

This skill guides the implementation of comprehensive error monitoring and observability solutions. It helps in setting up robust error tracking systems, configuring detailed alerts, implementing structured logging, and establishing workflows to ensure teams can quickly detect, group, and resolve production issues efficiently.

This skill is designed for advanced error detective work. It analyzes complex log streams, correlates stack traces across distributed systems, and detects anomalous error patterns. It helps identify root causes by correlating errors with system deployments and changes, providing actionable findings for immediate fixes and long-term prevention strategies.

This skill provides expert-level diagnostic capabilities for complex distributed systems. It specializes in analyzing production incidents, identifying deep root causes, and designing comprehensive observability solutions. Use this when investigating recurring errors, reviewing system logs/traces, and implementing preventative reliability measures.

This skill acts as an expert guide for implementing comprehensive error monitoring and observability solutions. It covers setting up robust error tracking systems, configuring intelligent alerts, implementing structured logging, and establishing advanced error grouping and recovery strategies. Use it to enhance production stability and accelerate issue resolution.

A comprehensive, AI-assisted methodology for diagnosing complex software errors in production environments. This skill guides users through the entire debugging lifecycle, from initial triage and gathering observability data (Sentry, DataDog, Jaeger) to generating hypotheses, selecting appropriate debugging strategies (Time-Travel, Chaos Engineering), and performing AI-powered root cause analysis. It culminates in proposing validated fixes and prevention measures.

Automates guidance for implementing error handler middleware in backend services, covering Node.js, Python, Go, microservices, databases, caching, messaging, and architecture best practices with production-ready code and validation.

This skill provides guidance on implementing robust error handling strategies to build highly resilient applications. It covers advanced patterns such as circuit breakers, retries, and handling asynchronous errors, ensuring that the application fails gracefully and provides excellent debugging experiences for both developers and end-users.