Skill UI

This skill acts as an expert risk manager, providing comprehensive guidance on monitoring portfolio risk, calculating R-multiples, and optimizing position limits. It covers advanced quantitative finance topics such as Value at Risk (VaR), correlation analysis, and stress testing using Monte Carlo simulations. Use it for systematic risk assessment, developing hedging strategies (options/futures), and implementing rigorous risk controls in trading workflows.

Execute controlled chaos experiments to proactively test system resilience, fault tolerance, and recovery capabilities. This toolkit simulates real-world failures, such as network latency, service crashes, resource exhaustion, and dependency outages, ensuring that microservices degrade gracefully and recover automatically. It is essential for modern distributed systems validation.

This expert simulates a compliance expert, specializing in regulatory requirements for software systems, including GDPR, HIPAA, SOC2, and PCI-DSS. It performs comprehensive audits, identifies compliance gaps, and generates actionable implementation plans, technical controls, and policy templates to ensure adherence to industry standards.

Guides senior data scientists through designing controlled experiments, engineering structured features, training ML models, and translating results into decisions using Python, R, SQL, and tools like Scikit-learn, XGBoost, and MLflow.

Automates Sensibo climate control via Composio's Rube MCP connectors, guiding through tool discovery, connection checks, and multi-step execution while handling sessions, schema compliance, and pagination for reliable workflows.

A comprehensive guide on optimizing Sentry observability costs. Learn techniques such as SDK-level error sampling, fine-grained performance tracing control, and event filtering using the `beforeSend` hook. These methods significantly reduce the volume of error and transaction data sent, allowing users to manage quotas and prevent overage charges without losing visibility into mission-critical production errors.

Configure GDPR-compliant data handling, PII scrubbing, and data retention policies within Sentry. This skill provides detailed instructions on implementing client-side `beforeSend` hooks and server-side scrubbing rules to securely redact sensitive data (passwords, emails, IP addresses, CC numbers). Essential for achieving compliance with regulations like GDPR, HIPAA, and meeting SOC 2 audit controls.

This guide provides comprehensive instructions for setting up and managing Sentry's enterprise-grade Role-Based Access Control (RBAC). It covers establishing the Organization-Team-Project hierarchy, integrating Single Sign-On (SSO) via SAML2, and automating user provisioning with SCIM. Use this when setting up large-scale organizations, enforcing granular team permissions, centralizing identity management, or ensuring regulatory compliance and audit logging.

This guide provides a comprehensive, environment-aware setup for Sentry in local development workflows. It details how to correctly route development events to separate DSNs, enable verbose debugging, and maximize data capture rates (e.g., setting sample rates to 1.0). Users learn to use `startSpan` for performance profiling and ensure that sensitive credentials are safely managed outside of source control.

A comprehensive guide to managing Sentry's event volume, quotas, and rate limits. Learn how to prevent 429 Too Many Requests errors and control costs by implementing client-side sampling (sampleRate/tracesSampleRate), using beforeSend filters to drop noisy errors, and understanding various quota types (Errors, Transactions, Replays). Essential for high-volume, cost-sensitive applications.

A comprehensive guide covering the principles of production-grade server management. Topics include process control (PM2, systemd), advanced monitoring strategies (Grafana, metrics), structured logging, scaling decisions (horizontal/vertical), and security best practices. It teaches systematic thinking for ensuring high availability, reliability, and scalability in complex systems.

Serve production-grade LLM APIs with vLLM, leveraging PagedAttention, continuous batching, quantization, and tensor parallelism to maximize throughput while keeping latency, GPU usage, and scalability under control for OpenAI-compatible deployments.