Skill UI

Implement comprehensive observability for Apollo.io API integrations. This skill provides structured instrumentation covering Prometheus metrics (request count, latency, rate limits, credits used), structured logging with PII redaction, and OpenTelemetry tracing. It ensures reliable tracking of API health, performance, and resource consumption.

This SDK provides comprehensive support for automatically instrumenting Node.js applications to collect observability data. It integrates distributed tracing, metrics, and logs using the OpenTelemetry standard, allowing seamless data export and monitoring within Azure Monitor. It supports various resource types and connection methods.

A comprehensive diagnostic guide for resolving the 10 most common Langfuse integration errors. This resource covers root causes, specific error codes (like 401 Unauthorized or connection timeouts), and provides tested solutions for debugging missing traces, authentication failures, and general LLM observability issues.

Phoenix is an open-source observability platform for tracing, evaluating, and monitoring LLM applications; use it to debug prompts, run dataset evaluations, build experiment pipelines, and watch production inference in real time.

This skill provides systematic, advanced diagnostic paths for complex Sentry issues. It addresses common pitfalls such as silently dropped events, failed source map resolution, gaps in distributed tracing, SDK memory leaks, and conflicts with other observability libraries. Use this guide when standard debugging fails and events disappear mysteriously.

A comprehensive guide to configuring Sentry error tracking and performance monitoring across modern application architectures. Learn how to implement coherent, end-to-end distributed tracing for monoliths, microservices, serverless functions (Lambda/Cloud Functions), event-driven systems, SPAs, and mobile applications, ensuring all application hops are monitored from a single source.

A comprehensive methodology for pinpointing the root cause of complex bugs, regressions, or unexpected behavior in large codebases. Techniques include binary search debugging, Git bisect for tracking regressions across commits, strategic data/control flow logging, component isolation, and advanced breakpoint strategies (conditional breakpoints, watch expressions). Ideal for scenarios where the bug source is unclear or difficult to reproduce.

A comprehensive, structured framework for conducting sophisticated Open Source Intelligence (OSINT) and cryptocurrency forensic investigations. This guide covers operational security (OpSec), target profiling, advanced transaction tracing across multiple blockchain layers (L1/L2), wallet analysis, and identifying linked digital assets. Use this methodology to guide systematic, multi-dimensional intelligence collection campaigns.