Skill UI

This skill provides advanced expertise in Infrastructure as Code (IaC) using Terraform and OpenTofu. It covers designing robust, reusable modules, managing complex multi-cloud state backends, and implementing enterprise-grade CI/CD pipelines. It specializes in governance, Policy-as-Code, and achieving GitOps compliance for full infrastructure automation.

Automates threat modeling guidance within Security Advanced: step-by-step best practices, compliance-ready code, and validation for enterprise security workflows.

A comprehensive tool for tracking and analyzing cryptocurrency derivatives markets. It aggregates key metrics such as funding rates, open interest, liquidations, and options flow across major CEX and DEX exchanges. Use it to identify arbitrage opportunities, gauge market sentiment, predict trend strength, and perform deep risk analysis on perpetual swaps and futures contracts.

TransformerLens is the standard library for performing mechanistic interpretability research on large language models. It provides clean interfaces to inspect and manipulate transformer internals—such as attention patterns, residual streams, and MLP outputs—via activation caching and HookPoints. This tool is essential for reverse-engineering model algorithms, performing causal tracing, and studying the internal circuits responsible for model behavior.

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 skill provides a comprehensive workflow for integrating TwinMind meeting transcription services into continuous integration/continuous deployment (CI/CD) pipelines. It automates the processes of meeting documentation, real-time transcription (using Ear-3), and structured action item extraction using advanced AI models like GPT-4 and Claude. Use this when setting up automated meeting intelligence operations or managing enterprise-level transcription workflows via API.

This skill is designed to help users optimize the operational costs of the TwinMind AI platform. It provides detailed usage monitoring and guidance for selecting the most appropriate subscription tier (Free, Pro, or Enterprise). Users can manage advanced features such as high-accuracy transcription (Ear-3) and AI summarization across multiple models (GPT-4, Claude, Gemini), ensuring efficient resource utilization and cost control for large-scale meeting AI operations.

This skill guides the implementation and management of meeting data within the TwinMind platform, ensuring adherence to GDPR compliance. It covers secure transcript storage, memory vault management, data export protocols, and deletion policies. Ideal for developers integrating complex meeting AI operations or managing enterprise-level data governance.

A comprehensive guide to setting up TwinMind Enterprise for large-scale corporate environments. This includes configuring on-premise deployment, integrating custom AI models (GPT-4, Claude, Gemini), and enabling Single Sign-On (SSO) using Okta. It is essential for implementing strict Role-Based Access Control (RBAC) and managing team-wide meeting intelligence and transcript sharing in a secure, enterprise setting.

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.

Configure the TwinMind AI platform across development, staging, and production environments. This setup ensures secure separation of accounts and manages API keys for robust meeting AI operations, supporting enterprise features like on-premise deployment and SSO integration.

Provides comprehensive observability for the TwinMind AI meeting system. This skill allows users to monitor critical performance metrics, including transcription quality (using Ear-3 model), meeting coverage, action item extraction accuracy, and memory vault health. It is essential for implementing robust, enterprise-grade AI workflows and managing the operational status of advanced meeting AI applications.