Skill UI

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 tool collects comprehensive diagnostic data for TwinMind issues. It gathers crucial information including environment details (OS, Node.js version, memory), API health status, network connectivity, and configuration snapshots. It is essential for generating detailed bug reports or preparing for technical support requests, helping developers quickly pinpoint the root cause of complex problems.

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.

This comprehensive guide details the process for managing service transitions on the TwinMind platform. It instructs users on how to audit current usage, export all key configurations (settings, integrations, webhooks), and execute plan upgrades (Pro or Enterprise) via both the dashboard and API. This ensures a seamless and controlled migration between service tiers.

Analyzes CORS configurations via the cors-policy-validator plugin to spot misconfigurations, validate headers or files, and report vulnerabilities so developers can secure web apps and APIs from unsafe cross-origin access.

This guide details how to implement environment isolation (dev, staging, prod) for GPU cloud deployments on Vast.ai. It uses environment variables and configuration classes to enforce separate API keys, budget caps, instance limits, and GPU whitelists for each deployment tier, ensuring efficient resource management and cost control.

Automates Vercel operations through Composio’s Rube MCP toolkit, covering deployment inspections, creation, env var updates, DNS, and project configuration via guided workflows.

This guide provides comprehensive methods for deploying, promoting, and managing Vercel applications in production environments. It covers advanced strategies like instant rollback, controlled rolling releases (canary deployments), multi-region function configuration, and integrating with headless CMS via deploy hooks. Use this when you require robust CI/CD practices, high availability, and predictable production traffic management.

Configure Vercel's advanced role-based access control (RBAC) for enterprise environments. This guide covers setting up granular team roles, managing project-level access groups, integrating SAML SSO for secure authentication, and enabling detailed audit logging. Use this when implementing strict security protocols and enforcing the principle of least privilege across your team's deployments and resources.