Skill UI

This skill is a powerful orchestrator designed to build complete full-stack applications from simple natural language requests. It analyzes user requirements, determines the optimal project type and technology stack, generates a detailed plan, and coordinates specialized agents (frontend, backend, database, etc.) to scaffold and build the entire project structure, accelerating the development lifecycle.

This skill is a powerful orchestrator designed to build complete full-stack applications from simple natural language requests. It analyzes user requirements, determines the optimal project type and technology stack, generates a detailed plan, and coordinates specialized agents (frontend, backend, database, etc.) to scaffold and build the entire project structure, accelerating the development lifecycle.

This skill automatically collects raw activity data (merged PRs, issues, commits, and optional Slack updates) from repositories. It formats this data using predefined templates, runs quality checks, and prepares a structured changelog draft. It can automatically commit the draft to a new branch and open a Pull Request (PR) for review, making it ideal for generating weekly or monthly release notes.

This orchestrator skill provides comprehensive core principles for game development, covering topics like the Game Loop, design patterns (State Machine, ECS), performance budgeting, and input abstraction. It guides users by routing them to specialized sub-skills based on required platforms (Web, Mobile, PC), dimensions (2D, 3D), and specialty areas (AI, Networking, Art). Ideal for structuring complex game projects from concept to implementation.

Gastown is a robust multi-agent orchestration system designed for Claude Code. It enables the simultaneous execution of multiple AI agents on complex projects. It manages the entire development lifecycle, from setting up workspaces and tracking work items (beads) to managing agent lifecycles (polecats/crew) and merging final code (Refinery). Use it when coordinating complex, parallel AI tasks.

This skill provides a comprehensive pattern for building robust, scalable, and fault-tolerant asynchronous video generation pipelines using Kling AI. It implements advanced software engineering patterns, including Redis queues (Producer/Consumer), State Machines, and event-driven callbacks. It is designed for managing complex, multi-step AI workflows—such as generate, extend, and download—ensuring reliable background task processing.

Mastering the full lifecycle of machine learning models from data ingestion to deployment. This expertise covers building robust, production-grade MLOps pipelines using orchestrators like Kubeflow, Airflow, or Prefect. Key skills include feature store implementation with Feast, rigorous data validation, experiment tracking (e.g., MLflow), model registry management, and automated deployment workflows. Essential for automating model training and ensuring reproducibility at scale.

This guide details advanced architectural patterns for building complex AI systems using multiple Language Model instances (agents). It addresses the single-agent context bottleneck by distributing work, enabling parallelism, and facilitating specialization across different subtasks. Key patterns include Supervisor/Orchestrator, Peer-to-Peer/Swarm, and Hierarchical designs, providing guidelines for context isolation and effective coordination protocols.

Enables Claude to orchestrate complex test workflows via the test-orchestrator plugin, defining dependencies, parallel execution, and smart selection so only affected suites run during CI/CD or manual optimization requests.

This guide outlines the comprehensive reference architecture for building advanced, AI-powered search and research applications, modeled after Perplexity. It covers three core tiers: a searchable service with model routing and caching, a citation pipeline for validation and rendering, and an orchestrator for multi-query research synthesis. Use this when designing complex, production-grade, search-augmented LLM integrations or reviewing advanced system patterns.

Base Refly ecosystem skill that routes user intents to domain-specific skills, runs workflows via the CLI, and automates multi-step tasks or pipelines by delegating execution to the Refly backend while providing CLI-specific triggers and commands.

An advanced workflow orchestrator designed to perform multi-phase, deep-dive schema optimization on large datasets (e.g., BigQuery exports). It systematically analyzes schema structure, identifies unused or redundant fields, assesses potential impact, and generates a comprehensive, actionable report with recommended optimization strategies and estimated savings.