Skill UI

Automates Winston AI operations through the Composio/Rube MCP workflow, covering tool discovery, connection checks, schema-compliant execution, session reuse, and pagination handling.

Retrieve AlphaFold’s AI-predicted protein models via UniProt IDs, download CIF/PDB coordinates, inspect confidence metrics, and feed them into structural analysis or drug-discovery pipelines.

Modal delivers cloud-native serverless Python with on-demand GPUs, persistent storage, and web endpoints to deploy ML workloads, batch jobs, and APIs without writing Dockerfiles.

Self-hosted open-source alternative to NotebookLM for organizing research, ingesting diverse sources, generating AI notes, running context-aware chats, performing vector search, producing multi-speaker podcasts, and automating workflows via a REST API.

PufferLib is a high-performance library designed for advanced reinforcement learning simulations and training. It excels in parallel environment simulation, offering optimized vectorization and native support for multi-agent systems. Utilizing algorithms like PuffeRL (optimized PPO+LSTM), it achieves millions of steps per second, significantly accelerating research and deployment across single-agent and multi-agent environments.

A comprehensive skill for leveraging massive pre-trained transformer models across diverse AI domains, including Natural Language Processing (NLP), Computer Vision (CV), and Audio. Use this skill for advanced tasks such as text generation, classification, question answering, summarization, object detection, and model fine-tuning on proprietary datasets. It provides streamlined pipelines and granular control for deployment.

Helps product managers diagnose whether AI workflows rely on indiscriminate context stuffing or deliberate context engineering, then apply bounded domains, retrieval, and Research→Plan→Reset→Implement practices to improve reliability and output quality.

This skill provides comprehensive techniques for optimizing prompts used with any Large Language Model (LLM). It teaches proven methodologies—including Role definition (R), Context setting (S), Constraints (C), Instructions (I), and Templates (T)—to transform vague inputs into precision-engineered instructions. Users can reliably achieve structured JSON output, implement Chain-of-Thought reasoning, reduce hallucinations, and minimize token usage, ensuring consistent and high-quality results across different AI platforms.

Build, run, and visualize multi-step AI generation workflows via muapi.ai. Translate natural language intents into runnable node graphs, discover or edit existing pipelines, and execute them interactively or through the CLI with automated monitoring.

Analyze travel health risks for destinations, recommend vaccines and travel medicine, and generate multilingual emergency medical cards using WHO/CDC-style guidance. Useful for pre-trip planning, risk assessment, and post-travel monitoring.

Coordinates discovery, matching, and workflow orchestration across agent ecosystems, automatically scanning SKILL.md, ranking relevant skills, and executing multi-step plans for complex requests.

A specialized skill for generating hyper-realistic, humanized images using Google AI Studio (Gemini). It simulates the imperfections of real photography—such as natural lighting, slight camera shake, and depth of field—to create content that looks genuinely captured by a smartphone. Ideal for creating high-quality assets for social media (influencer style) or educational materials.