Skill UI

This SDK provides comprehensive, production-ready patterns for interacting with the OpenEvidence clinical evidence API. It enables developers to efficiently query medical literature, retrieve clinical guidelines, and generate evidence-based recommendations. Key features include a singleton client for consistent authentication, robust error wrappers (handling retries, invalid keys), and structured data models designed to ensure audit compliance and detailed citation provenance in complex healthcare applications.

This guide provides essential security protocols and coding best practices for integrating with OpenEvidence, a platform processing Protected Health Information (PHI). It covers mandatory topics such as HIPAA compliance, API key management, webhook signature verification, input validation, and data redaction, ensuring all interactions are secure and audit-compliant.

A comprehensive guide maintained by Supabase for optimizing Postgres performance. It provides critical rules and best practices across query performance, schema design, connection management, and security (including RLS). Use this skill when writing, reviewing, or optimizing complex SQL queries, database schemas, or configurations to ensure optimal database health and performance.

This skill provides comprehensive expertise for senior database administrators to optimize and manage PostgreSQL databases at an advanced level. Use it for deep query analysis via EXPLAIN ANALYZE, implementing advanced features like JSONB indexing, configuring streaming or logical replication, and maintaining database health through VACUUM tuning and monitoring pg_stat views. Ideal for building highly available, high-performance, and resilient system architectures.

Monitor the operational health of PostHog integrations by tracking critical metrics. This skill checks event ingestion rates, feature flag evaluation latency, and monitors billing volume consumption. It also provides rules for Prometheus/Grafana alerting, ensuring data pipelines remain stable and alerting on potential performance bottlenecks or exceeding API limits.

An advanced skill for Scrum Masters that uses Python scripts to analyze raw sprint data exported from tools like Jira. It provides comprehensive insights including Monte Carlo velocity forecasting, a multi-dimensional team health score (0-100), and tracking of action items and recurring themes from retrospectives. Ideal for process improvement, sprint planning, and stakeholder reporting.

This comprehensive skill guides the full lifecycle management of Supabase projects in a production environment. It covers essential DevOps practices, including running database migrations, deploying Edge Functions, managing secrets, implementing zero-downtime blue/green rollouts, and executing robust rollback procedures and post-deployment health checks. Ideal for ensuring stable and reliable production deployments.

Use this resource to implement comprehensive end-to-end monitoring and observability for Supabase projects. It guides users through analyzing API metrics, diagnosing slow database queries using pg_stat_statements, managing log drains for external aggregation, and setting up custom alerts, ensuring optimal project health and performance.

A comprehensive skill to identify, analyze, prioritize, and track technical debt across large codebases. It provides three interconnected tools: a Debt Scanner, a Debt Prioritizer (using cost-of-delay frameworks), and a Debt Dashboard. This system helps engineering teams make data-driven decisions to balance new features with necessary maintenance and refactoring work, ensuring the long-term sustainability of software systems.

This tool collects comprehensive diagnostic data for TwinMind issues. It gathers crucial information including environment details (OS, Node.js version, memory), API health status, network connectivity, and configuration snapshots. It is essential for generating detailed bug reports or preparing for technical support requests, helping developers quickly pinpoint the root cause of complex problems.

A comprehensive guide for deploying Machine Learning training jobs and inference services on the Vast.ai GPU cloud. This skill covers the entire deployment lifecycle, including optimizing Docker images for performance, creating automated provisioning scripts using the Vast.ai CLI, implementing robust data transfer strategies (SCP, rsync), and performing post-deployment health checks.

This comprehensive bundle collects all necessary diagnostic information for troubleshooting and creating support tickets for Windsurf. It gathers environment details, redacted configuration files, activity logs, and workspace health into a single, compressed archive. Use this tool when encountering persistent bugs or when technical support requires deep system analysis.