Skill UI

A comprehensive guide and implementation patterns for constructing sophisticated autonomous AI agents. It details the core 'Observe-Think-Decide-Act' agent loop, multi-model orchestration strategies, and robust tool design principles (like file I/O and function calling). Ideal for building complex, highly capable agents that require advanced planning, reasoning, and external tool interaction.

A comprehensive guide and implementation patterns for constructing sophisticated autonomous AI agents. It details the core 'Observe-Think-Decide-Act' agent loop, multi-model orchestration strategies, and robust tool design principles (like file I/O and function calling). Ideal for building complex, highly capable agents that require advanced planning, reasoning, and external tool interaction.

Bridges frozen vision encoders and LLMs for high-quality image captioning, VQA, retrieval, and multimodal chat, enabling zero-shot reasoning without fine-tuning and offering efficient Q-Former training.

BlockRun acts as a universal gateway to advanced AI capabilities. It routes user requests to specialized models (e.g., DALL-E for image generation, Grok for real-time X/Twitter data, GPT-5.2 for complex reasoning) using a micropayment wallet system. This allows the agent to execute tasks autonomously by paying for necessary services, ensuring high capability and managing user spending.

Use before creative or constructive work (features, architecture, behavior). Transforms vague ideas into validated designs through disciplined reasoning and collaboration.

Empowers building AI agents that perceive screens, plan via vision-language reasoning, and control mouse/keyboard for desktop automation, with attention to sandboxing and safety across Anthropic, OpenAI, and open-source paradigms.

Provides expert guidance on designing, implementing, and optimizing cutting-edge computer vision pipelines. Expertise spans real-time object detection (YOLO26), advanced promptable segmentation (SAM 3), and leveraging Vision Language Models (VLMs) for complex visual reasoning. Ideal for building high-performance systems in robotics, autonomous vehicles, and industrial inspection, including 3D reconstruction and edge deployment optimization.

Applies empirically grounded cognitive science frameworks to help CS and AI researchers generate genuinely novel directions through bisociation, analogical reasoning, constraint shifts, and problem reformulation workflows.

A comprehensive guide detailing advanced strategies for migrating complex, rule-based automations from platforms like Zapier, Make, n8n, or custom codebases to Lindy AI. It teaches users how to redesign workflows, leveraging AI agents to replace rigid conditional logic with adaptable reasoning, ensuring a smooth and intelligent transition across multiple phases.

This comprehensive guide provides production-ready patterns for building advanced LLM applications. It details the entire RAG pipeline, covering document ingestion, various chunking strategies, and advanced retrieval methods (Hybrid, Multi-query). Furthermore, it covers sophisticated agent architectures, such as ReAct, enabling complex reasoning and tool use. Ideal for developers designing enterprise-grade AI systems.

This skill simulates an expert prompt engineer, specializing in optimizing prompts for Large Language Models (LLMs). It applies advanced techniques such as Constitutional AI, Chain-of-Thought reasoning, and model-specific tuning. Use this tool to transform basic instructions into production-ready, high-performance prompts, significantly boosting accuracy, reducing hallucinations, and optimizing token usage.

Loki Mode is a multi-agent autonomous startup system that progresses PRD to production with zero human intervention, orchestrating research-enhanced components such as OpenAI SDK, DeepMind, Anthropic, AWS Bedrock, and agent tooling while enforcing RARV reasoning and efficiency tracking.