Skill UI

This guide identifies and explains common anti-patterns and critical pitfalls encountered when building applications on the Replit platform. Topics include data persistence, secret management, networking bindings, and environment configuration. Use this resource when conducting code reviews, onboarding new developers, or auditing existing Replit applications for best practices.

This skill provides a comprehensive toolkit for calculating essential portfolio risk metrics. It includes Value at Risk (VaR), Conditional VaR (CVaR), Sharpe Ratio, Sortino Ratio, and drawdown analysis. It is crucial for measuring overall portfolio risk, implementing risk limits, building sophisticated risk dashboards, and ensuring compliance for regulatory reporting in finance.

This comprehensive tool validates web applications against WCAG 2.1/2.2 accessibility standards. It combines automated scanning using industry-leading tools (like axe-core, Lighthouse) with crucial manual checks for keyboard navigation, ARIA implementation, and color contrast. It is essential for QA teams and developers who must ensure high usability and accessibility for all users, including those relying on screen readers.

Conducts detailed accessibility audits for web apps via the accessibility-test-scanner plugin, verifying WCAG 2.1/2.2 compliance, ARIA usage, keyboard navigation, and screen reader compatibility while providing remediation guidance when accessibility or compliance checks are requested.

Automates guidance for building SDK wrappers within API integration workflows, offering best-practice patterns, code scaffolding, validation, and configuration details to streamline third-party API, webhook, and OAuth onboarding.

Automates setting up synthetic monitoring by defining critical endpoints, crafting uptime, transaction, and API scenarios, and configuring alerts/dashboards to keep application performance and availability under proactive watch.

A specialized reverse-engineering skill designed to extract comprehensive functional and non-functional specifications from existing, undocumented, or legacy codebases. It operates by analyzing code structure, tracing data flows, and identifying observable behaviors. The output is structured using EARS (Easy Approach to Requirements Syntax), providing clearer requirements documentation, architectural diagrams, and dependency maps for onboarding or system modernization.

A comprehensive guide detailing the most common and critical mistakes when developing with Supabase. Covers severe security issues (like exposing service role keys or missing RLS), data integrity failures, and performance bottlenecks (connection pooling, N+1 queries). Essential for code review, onboarding new developers, or auditing existing Supabase projects to ensure secure and robust applications.

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.

TensorBoard delivers a unified interface to track training metrics, debug network behavior, compare experiments, inspect model graphs, and profile performance for PyTorch or TensorFlow workflows.

Assists with tensorboard visualizer tasks for ML training by guiding setup, best practices, and experiment tracking whenever tensorboard visualization is mentioned, producing production-ready configs and validated outputs.