Skill UI

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.

This comprehensive skill guides users through the entire debugging lifecycle, from reproducing elusive bugs to tracing the root cause, implementing permanent fixes, and preventing future regressions. It covers advanced techniques like binary search, time travel debugging, and handling common patterns such as race conditions and null values, ensuring professional and systematic troubleshooting for any production issue.

This skill generates a comprehensive, structured medical summary card for quick access during emergencies, travel, or hospital visits. It extracts critical user data, including severe allergies, active medications, chronic conditions, implants, and emergency contacts. Supports multi-format output (HTML, JSON, PDF) and prioritizes information by medical urgency (P0-P2) for rapid deployment in critical situations.

Analyze travel health risks for destinations, recommend vaccines and travel medicine, and generate multilingual emergency medical cards using WHO/CDC-style guidance. Useful for pre-trip planning, risk assessment, and post-travel monitoring.

This skill guides users on querying Azure Monitor activity and sign-in logs using KQL to detect sophisticated security threats. It covers identifying suspicious administrative activities, impossible travel scenarios, privilege escalation attempts, and unauthorized resource modifications. Ideal for Security Operations Center (SOC) analysts building advanced threat hunting rules or developing cloud SIEM detections.

Utilizes User and Entity Behavior Analytics (UEBA), statistical baselines, and machine learning models to monitor authentication logs. This skill identifies sophisticated security threats such as impossible travel, credential stuffing, brute force attacks, and compromised accounts in real-time. Essential for security operations and identity access management.

This skill detects compromised cloud credentials by analyzing anomalous API activity, impossible travel patterns, and unauthorized access indicators across AWS, Azure, and GCP. It integrates findings from GuardDuty, Defender for Identity, and Security Command Center to provide comprehensive threat visibility and assist in incident response and scope assessment.

This skill outlines a comprehensive methodology for detecting compromised email accounts in Microsoft 365 and Google Workspace. It analyzes critical indicators such as unauthorized inbox rule creation (e.g., forwarding rules, deletion rules), suspicious sign-in locations (impossible travel), and unusual API access patterns using Microsoft Graph and Unified Audit Logs. It is essential for threat hunting and incident response (IR) to mitigate Business Email Compromise (BEC) and account takeover.

This skill performs User and Entity Behavior Analytics (UEBA) to identify anomalous user activities such as impossible travel, unusual access patterns, and privilege abuse. It establishes behavioral baselines using SIEM logs and statistical analysis, helping SOC teams detect insider threats and compromised accounts by flagging deviations from normal user behavior. Use when monitoring security hygiene and suspicious activity is critical.

A library providing structured error handling for Go applications, moving beyond standard Go errors. It uses a fluent builder pattern to attach rich metadata—including domain context, user IDs, stack traces, custom attributes, and machine-readable error codes—directly to the error object. This ensures that crucial contextual data travels up the call stack, making errors highly diagnosable for on-call engineers and compatible with APM tools like Datadog or Sentry.

Creates a Google Sheets spreadsheet prepopulated with headers, a sample expense entry, and sharing permissions so teams can immediately start logging and reviewing travel costs.

A comprehensive guide to ensuring robust state management for LangGraph agents. This skill addresses common checkpointing pitfalls (like missing thread_id or non-JSON serializable state) and details best practices for implementing reliable state persistence using MemorySaver or PostgresSaver. It covers thread discipline, schema migration, and time-travel debugging for production-ready applications.