Skill UI

Automates guidance for streaming inference setup, covering best practices in ML deployment, serving, monitoring, and production-ready configurations whenever you ask about streaming inference patterns or implementation.

Provides a structured workflow for defining agent-agnostic subagents with isolated context, covering purpose definition, metadata configuration, prompt writing, and common specialist patterns for verification, debugging, security auditing, and review.

Assists with tensorboard visualizer tasks for ML training by guiding setup, best practices, and experiment tracking whenever tensorboard visualization is mentioned, producing production-ready configs and validated outputs.

Automates TensorFlow SavedModel deployment support with step-by-step guidance, best-practice patterns, production-ready code/config generation, and validation for serving, monitoring, and optimization scenarios.

Assists with torchscript exporter tasks for ML deployment, offering automated guidance, code/config generation, and validation against industry standards whenever torchscript exporters are mentioned.

Automates generating TorchServe deployment configurations with guided best practices for model serving, MLOps pipelines, inference, and production monitoring so ML deployment workflows stay consistent and reliable.

Automates Triton inference config guidance for ML deployment, covering serving, MLOps pipelines, monitoring, and production-ready configurations aligned with best practices.

Guides Claude to automatically tune machine learning model hyperparameters via grid, random, or Bayesian search, generating runnable Python code, executing validations, and reporting best configurations plus performance metrics for accuracy or other goals.

This guide provides comprehensive steps for deploying TwinMind integrations into production environments. It covers configuring the Chrome extension, setting up mobile app access, and managing API keys. TwinMind utilizes advanced AI models (including Ear-3 for transcription and GPT-4/Claude/Gemini for summarization) to provide real-time meeting transcription, summarization, and action item extraction. Ideal for professional teams managing high-volume AI meeting operations.

This comprehensive guide details the setup and authentication process for the TwinMind AI suite. It covers installing the Chrome extension, setting up mobile applications, integrating with Google/Microsoft calendars, and configuring API access. Use this skill when initializing TwinMind into a professional workflow for automated meeting transcription, note-taking, and data synchronization.

This guide assists in migrating meeting AI workflows from competing tools (such as Otter.ai, Fireflies) to TwinMind. It provides a deep dive into setting up the enterprise environment, covering prerequisites, API configuration, and utilizing advanced AI models (GPT-4, Claude, Gemini) for robust transcription and intelligent summarization. Ideal for managing large-scale meeting intelligence operations.

This skill outlines security best practices for the TwinMind AI meeting assistant. It covers crucial aspects like on-device audio processing, encrypted cloud backups, and managing microphone permissions. Use it when setting up new TwinMind instances or managing AI operations to ensure data privacy, compliance, and robust security for sensitive meeting data.