Skill UI

This skill provides comprehensive scripts and workflows to automatically identify and remove unused AWS resources across multiple services (EBS, S3, EC2, EIPs). By automating the cleanup of orphaned volumes, old snapshots, and stale data, users can eliminate cloud waste, significantly optimizing their AWS expenditure and ensuring a cost-efficient infrastructure.

This guide provides comprehensive strategies to optimize costs associated with Clerk authentication services. It details understanding the MAU pricing model, implementing route-level authentication controls, utilizing caching techniques to reduce API calls, and scripting the cleanup of inactive users, helping maintain compliance and controlling expenditure.

This skill functions as a dedicated dependency security expert, specializing in auditing project dependencies. It analyzes codebases for known security vulnerabilities, license compliance issues, outdated packages, and overall supply chain risks. It provides comprehensive, actionable remediation strategies and detailed risk reports to keep software supply chains secure and compliant.

This expert analyzes and refactors existing codebases to enhance quality, maintainability, and performance. It specializes in applying clean code principles, SOLID design patterns, and modern software engineering best practices. Use it to clean up technical debt, simplify complex modules, or prepare a codebase for new feature development.

A comprehensive expert system for analyzing software codebases to identify, quantify, and prioritize technical debt across various dimensions (code, architecture, testing, infrastructure). It provides detailed metrics, impact assessments (development velocity, quality loss), and actionable, prioritized remediation roadmaps with clear ROI projections.

A comprehensive guide to production-ready patterns for the Databricks Python SDK. This skill covers essential best practices including singleton client initialization, structured error handling with typed exceptions, context-managed cluster lifecycle control (ensuring cleanup), and implementing type-safe job definitions. It is essential for building robust, maintainable, and idiomatic integrations with the Databricks platform.

Comprehensive guide for setting up a complete local development stack for Documenso integrations. It covers project structure, environment variable configuration, running self-hosted services using Docker (PostgreSQL, MailHog), and implementing utility scripts for connection verification and test data cleanup.

Analyzes local git branches and worktrees, groups related prefixes, verifies merges or squash history, and safely prompts before deleting merged, superseded, or gone branches. Use when stale local branches and worktrees need cleanup without affecting remote.

This skill provides comprehensive methods for managing the entire data lifecycle of LLM observability platforms like Langfuse. Functions include exporting detailed traces and scores, configuring retention policies (e.g., automatic data cleanup), handling GDPR subject requests (access and erasure), and anonymizing Personally Identifiable Information (PII) for secure analytics. Essential for maintaining regulatory compliance in AI applications.

Summarizes React’s official guidance on when to use or avoid useEffect by highlighting derived state handling, expensive calculations, subscriptions, and cleanup strategies for data fetching.

Automates environment prep, service orchestration, and cleanup for executing integration test suites, covering database setup, migrations, and optional coverage reports.

This guide provides comprehensive, actionable methods to audit and significantly reduce Supabase operational costs. It covers advanced database tuning (vacuuming, index cleanup, bloat management), efficient storage lifecycle management, connection pooling strategies, and optimal plan selection. Use this when analyzing high billing reports, identifying resource waste, or implementing robust cost-saving measures in a cloud environment.