Skill UI

This guide provides a deep dive into migrating existing presentation content (from PowerPoint, Google Slides, Canva, etc.) to the modern, AI-powered format of Gamma. It details a robust, multi-step workflow: content extraction, content cleaning, and batch regeneration using scripting methods. This approach ensures that the core content is preserved while benefiting from Gamma's superior AI formatting capabilities, moving beyond simple file imports and guaranteeing better results than the original source files.

Generates production-ready Docker Compose configurations for multi-container apps by defining services, networks, volumes, health checks, and resource limits based on user architecture input.

Guides multi-agent workflows through an iterative context retrieval loop—dispatching broad queries, evaluating relevance, refining criteria, and looping up to three times so sub-agents gather exactly the files they need without overwhelming limits.

This guide provides a comprehensive local development environment setup for Internationalization (i18n) using Lokalise. It details configuring the project structure, implementing CLI scripts for synchronizing source strings (push) and translations (pull), setting up file watching for hot reloading, and generating mock translations for robust offline testing. Ideal for developers managing multi-language applications.

This comprehensive script suite provides a structured, multi-step audit for internationalization (i18n) integrations using Lokalise. It automates crucial checks, including verifying translation coverage across all required locales, detecting key synchronization issues (missing or orphaned keys) between the source code and the Translation Management System (TMS), and validating the format of localized files. Use this utility before any major production deployment or go-live phase to ensure localization readiness.

Provides a comprehensive, production-ready reference architecture for integrating Lokalise Translation Management System (TMS) into web applications. This guide covers the entire end-to-end translation lifecycle, including best-practice project layouts, file organization for i18n, CI/CD workflows (build-time vs. OTA paths), and necessary API client implementations. Use this when establishing new multi-language support or standardizing localization practices across a team.

Memory provides persistent context across multiple coding sessions. It stores crucial project decisions, user preferences (like preferred package managers or specific libraries), and architectural conventions in a local memory file. This ensures that the AI maintains consistency, recalls past choices automatically, and applies project-specific rules without needing constant reminders, significantly improving workflow continuity and reliability.

This skill provides comprehensive, multi-layered diagnostic scripts for resolving complex and intermittent issues with the Perplexity Sonar API. It allows users to test connectivity (DNS, TLS, TCP), profile API latency, validate citation stability, and verify search recency filters. It is crucial when standard troubleshooting methods prove insufficient for diagnosing hard-to-replicate API bugs or performance regressions.

This skill enables persistent, file-based planning for AI agents, acting as an external, reliable working memory on disk. By utilizing dedicated markdown files (task_plan.md, findings.md, progress.md), it allows complex, multi-step projects, research tasks, or coding sprints to survive context loss and session resets. It is essential for maintaining state and tracking progress across long-running, intensive workloads.

A comprehensive guide to selecting the optimal architecture for Replit applications. It compares three scaling models—single-file scripts (prototypes), modular apps (MVPs), and multi-service systems (large scale)—to help developers choose the correct database, storage, and deployment strategy as their project grows.

This skill provides comprehensive guidance on selecting the optimal workspace architecture for Windsurf, adapting to various project scales. Whether managing small solo projects, large monorepos, or complex multi-service, polyglot systems, it outlines strategies for structuring file systems and configuring rules. The goal is to ensure that AI tools receive accurate and focused project context, maximizing developer efficiency.

A powerful agentic workflow for complex software development. Cascade Write mode acts as an autonomous coding agent, allowing users to build features, refactor code across multiple files, run terminal commands, and debug errors—all from a single natural language prompt. Ideal for full-stack development, complex system building, and large-scale code refactoring.