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Browser automation for AI agents via inference.sh. Navigate web pages, interact with elements using @e refs, take screenshots, record video. Capabilities: web scraping, form filling, clicking, typing, drag-drop, file upload, JavaScript execution. Use for: web automation, data extraction, testing, agent browsing, research. Triggers: browser, web automation, scrape, navigate, click, fill form, scree

Master AI-powered test automation with modern frameworks,

Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.

Generate scholarly bilingual (English + Traditional Chinese) explanations for classical Chinese verses. Covers Yilin, I Ching, Tang poetry.

X/Twitter content intelligence with a social graph. Scout reply opportunities, pulse- check topic lanes, track competitors, mirror your accounts, prospect clients. Graph- first — built around accounts and topics YOU care about, not generic search. Use when user says 'xray', 'x research', 'search x', 'scout', 'pulse', 'track', 'mirror', 'prospect', '/xray', or needs real-time X discourse / engageme

Python SDK for inference.sh - run AI apps, build agents, and integrate with 150+ models. Package: inferencesh (pip install inferencesh). Supports sync/async, streaming, file uploads. Build agents with template or ad-hoc patterns, tool builder API, skills, and human approval. Use for: Python integration, AI apps, agent development, RAG pipelines, automation. Triggers: python sdk, inferencesh, pip i

Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.

This skill should be used when the user asks to "understand context", "explain context windows", "design agent architecture", "debug context issues", "optimize context usage", or discusses context components, attention mechanics, progressive disclosure, or context budgeting. Provides foundational understanding of context engineering for AI agent systems.

Guia para criar chatbots ChatKit de nível de produção que integram o SDK de Agentes OpenAI com ferramentas MCP e backends personalizados. Use ao construir chatbots com IA com capacidades especializadas, execução de tarefas em tempo real e isolamento de usuário para qualquer aplicação.

Document software architecture using ARCHITECTURE.md and docs/*.md files with Mermaid diagrams. Use proactively when ARCHITECTURE.md exists in project root, or invoke to create initial architecture documentation. Covers system design, data flows, component relationships, and code organization with references to key entry points and abstractions.

Um sistema de geração de UI que utiliza image-2, a cadeia de ferramentas MCP e engenharia de prompt para criar um ciclo fechado multimodal, gerando interfaces web, telas de aplicativos e outros elementos de design. Ele integra princípios de design de fontes autorizadas e oferece capacidades únicas de ancoragem visual e validação multimodal.

SDK de Transcrição Azure AI para Python, utilizado para transcrição de fala para texto em tempo real e em lote, com suporte a carimbos de data/hora e diarização.