Skill UI

This skill provides comprehensive guidance on implementing distributed tracing using industry standards like OpenTelemetry and tools such as Jaeger/Tempo. It enables developers to monitor the end-to-end lifecycle of a request across multiple microservices. Use this skill to debug latency issues, visualize complex service dependencies, pinpoint performance bottlenecks, and accurately trace error propagation in highly distributed systems.

Curated guidelines covering idiomatic Go error handling, interface design, concurrency patterns, context propagation, testing, and module management for reliable team codebases.

This skill provides comprehensive guidelines for writing idiomatic, robust, and production-ready error handling in Go. It covers best practices for error creation, proper wrapping using `%w`, inspection techniques with `errors.Is` and `errors.As`, adhering to the single handling rule, and utilizing structured logging with `slog`. Use it when auditing, reviewing, or writing new Go code to ensure reliable error propagation and logging.

A type-safe, declarative implementation of ReactiveX in Go. This library enables robust handling of infinite, asynchronous event streams (like WebSockets or tickers) by providing composable operators, automatic backpressure management, and error propagation. It is designed to replace complex, error-prone manual channel and goroutine wiring, allowing developers to build predictable, real-time, event-driven pipelines.

This guide teaches how to build robust, production-grade ReAct agents using LangGraph 1.0's `create_react_agent`. It specifically addresses common agent failure modes, such as preventing infinite loops (recursion caps) and ensuring proper error propagation. Learn to define typed tools using Pydantic, manage state with checkpointers, and set precise recursion limits. Perfect for users migrating from legacy AgentExecutor or building reliable, multi-step tool-calling workflows.

Detects error propagation and chain failures in agent workflows. Identifies vulnerabilities like single-point breakdowns, unbounded retries, and unsafe data propagation to ensure system stability and safety during multi-step operations.

Implement distributed tracing with Jaeger and Tempo for request flow visibility across microservices. Configure OpenTelemetry SDK and exporters to diagnose latency and errors. Ensure secure context propagation without logging sensitive data. Verify trace spans and sampling strategies for production observability.