Pixel Art Exporter

Pixel Art Professional

willibrandon

Apply advanced pixel art techniques including dithering, palette optimization, shading, antialiasing, and color theory. Use when the user mentions "dithering", "dither", "Bayer", "Floyd-Steinberg", "palette", "colors", "reduce colors", "optimize palette", "color limit", "shading", "shadows", "highlights", "lighting", "light source", "antialiasing", "smooth", "smoothing", "anti-alias", "AA", "color ramp", "gradient", "hue shifting", "saturation", "value", "contrast", or wants to "refine", "polish", "improve", "enhance", "make better", "add depth", "add dimension" to existing pixel art. Trigger on retro palette names (NES, Game Boy, C64, PICO-8), texture terms ("metal", "fabric", "stone", "wood"), and visual quality terms ("professional", "clean", "smooth", "vibrant").

javascript-fundamentals

manutej

Core JavaScript language features, patterns, and best practices including ES6+ syntax, async/await, closures, prototypes, and modern development patterns

langchain-orchestration

manutej

Comprehensive guide for building production-grade LLM applications using LangChain's chains, agents, memory systems, RAG patterns, and advanced orchestration

langchain4j-ai-services-patterns

giuseppe-trisciuoglio

Comprehensive guide for building declarative AI Services with LangChain4j using interface-based patterns, annotations, memory management, tools integration, and advanced AI application patterns. Use when implementing AI-powered features with LangChain4j in Java applications.

langchain4j-tool-function-calling-patterns

giuseppe-trisciuoglio

Tool and function calling patterns with LangChain4j. Define tools, handle function calls, and integrate with LLM agents. Use when building agentic applications that interact with tools.

langchain4j-rag-implementation-patterns

giuseppe-trisciuoglio

Retrieval-Augmented Generation (RAG) implementation patterns with LangChain4j. Retrieve documents, embed them, and augment LLM prompts with context. Use when building knowledge-powered AI applications.

langchain4j-mcp-server-patterns

giuseppe-trisciuoglio

Model Context Protocol (MCP) server implementation patterns with LangChain4j. Use when building MCP servers to extend AI capabilities with custom tools and resources.

prompt-engineering-patterns

camoneart

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.

langchain-architecture

camoneart

Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns. Use when building LangChain applications, implementing AI agents, or creating complex LLM workflows.

Cloudflare Manager

qdhenry

Comprehensive Cloudflare account management for deploying Workers, KV Storage, R2, Pages, DNS, and Routes. Use when deploying cloudflare services, managing worker containers, configuring KV/R2 storage, or setting up DNS/routing. Requires CLOUDFLARE_API_KEY in .env and Bun runtime with dependencies installed.

data-ml

baz-scm

Competence in data analytics and machine learning, enabling developers to build data-driven features and integrate AI/ML capabilities.

senior-prompt-engineer

alirezarezvani

World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-thought, and AI evaluation. Includes RAG optimization, agent design, and LLM system architecture. Use when building AI products, optimizing LLM performance, designing agentic systems, or implementing advanced prompting techniques.