Skill UI

A comprehensive guide providing step-by-step instructions for upgrading Langfuse SDK versions (v3 to v5) and migrating between major API changes. It covers best practices for both TypeScript/JavaScript and Python implementations, focusing on adopting OpenTelemetry standards to ensure seamless LLM observability integration.

This guide provides comprehensive, step-by-step instructions for installing and configuring the Manifest observability plugin for your AI agent. Users can use this skill to set up telemetry, connect the agent to Manifest for real-time monitoring, manage API keys, and troubleshoot various connection issues, ensuring full system observability.

Documents setting up OpenTelemetry tracing/metrics, Prometheus/Grafana monitoring, structured logging, and alerting rules so teams can instrument services, track performance, and respond to incidents.

Expert skill in designing and implementing comprehensive observability stacks for enterprise microservices. Covers advanced monitoring (Prometheus, Grafana), distributed tracing (Jaeger, OpenTelemetry), centralized logging (ELK, Splunk), and defining SLIs/SLOs. Ideal for ensuring high availability, mastering incident response, and performing reliability engineering on large-scale, distributed applications.

This skill simulates an expert performance engineer capable of diagnosing complex bottlenecks across the entire technology stack. It covers modern observability techniques (OpenTelemetry, APM), advanced profiling (CPU, Memory, I/O), and sophisticated load testing strategies (k6, Chaos Engineering). Use this when optimizing scalability, reducing latency, improving throughput, or architecting highly reliable, performant distributed systems in cloud environments.

This guide provides a comprehensive setup for Vercel observability. It covers enabling built-in analytics, collecting detailed runtime logs, implementing structured logging, configuring external log drains (e.g., Datadog, Sentry), and integrating OpenTelemetry tracing. Use this when monitoring production deployments and setting up robust error tracking.

A comprehensive guide to securing development workspaces using Windsurf. This skill teaches how to apply best practices for workspace isolation, prevent sensitive data (secrets, PII) from leaking into AI indexes, manage telemetry, and ensure compliance by configuring exclusion files and security rules.

A comprehensive guide for designing and implementing production-grade microservices using gRPC in Go. Covers best practices for API contract standardization with Protobuf and Buf, securing service-to-service communication via mTLS, and integrating deep observability using OpenTelemetry interceptors. Ideal for building high-performance, reliable internal APIs.

This framework provides a systematic methodology for cybersecurity professionals to transform raw threat intelligence, observed attack patterns, and environmental telemetry into verifiable, testable hunting hypotheses. It guides the end-to-end process, from hypothesis formulation and data identification across SIEM/EDR systems, to deep correlation and reporting, enabling proactive threat detection and scope assessment.

This skill provides a comprehensive framework for building automated pipelines that ingest, normalize, and operationalize threat intelligence (TI). It connects diverse sources—including STIX/TAXII feeds, open-source feeds (e.g., Abuse.ch), and commercial TI platforms—into SIEM and security tools. Use this when SOC teams need to automate the entire lifecycle of IOC ingestion, scoring, and real-time matching against network telemetry.

This utility provides a comprehensive framework for proactive threat hunting, focusing on detecting advanced and suspicious PowerShell execution patterns. It covers common attacker techniques such as encoded command usage, download cradles (IEX), AMSI bypass attempts, and constrained language mode evasion. It is designed for security analysts during incident response and threat intelligence validation, requiring EDR and SIEM telemetry.

This guide details how to implement advanced SIEM correlation rules to detect sophisticated Advanced Persistent Threats (APTs). By chaining multiple event types—including Windows authentication events, process execution telemetry, and network connection logs—across hosts, users can surface complex attack sequences that are invisible to single-event detections. It utilizes Splunk SPL and Sigma rule formats for robust security posture enhancement.