Skill UI

This skill automates the setup and configuration of Ollama, allowing users to deploy Large Language Models (LLMs) locally. It performs system assessment (OS, GPU, RAM), selects optimal models based on hardware availability, and handles installation across macOS, Linux, and Docker. Use this when you require free, self-hosted AI alternatives, need offline inference capabilities, or wish to eliminate reliance on costly hosted API services.

This comprehensive runbook provides rapid, structured procedures for incident response on Vast.ai cloud GPU instances. It covers common failure scenarios like spot preemption, training job crashes, and GPU hardware issues. Users can follow the steps for triage, mitigation, recovery, and postmortem analysis to minimize downtime and ensure computational continuity.

This comprehensive guide outlines security best practices for utilizing Vast.ai's cloud environment. It covers secure API key management, hardening SSH access to GPU instances, implementing proper data cleanup before instance destruction, and adhering to robust network security protocols. Use this when setting up, auditing, or deploying sensitive AI/ML workloads on shared cloud hardware.

Cirq is Google Quantum AI’s Python framework for building, simulating, and deploying noise-aware quantum circuits on both simulators and real hardware, complete with experiment templates, transformation utilities, and hardware-specific toolkits.

Qiskit is the world's leading open-source framework for building, optimizing, and executing quantum circuits. It provides comprehensive capabilities for quantum error mitigation, running algorithms on diverse hardware backends (including IBM Quantum and simulators), and supporting applications in chemistry and machine learning. Essential for researchers entering the quantum computing field.

This skill monitors the performance of Claude Code and the local operating system. It diagnoses slowdowns, measures CPU/RAM/Disk usage, checks API latency, and generates detailed system health reports. It helps determine if the bottleneck is local hardware or the remote API connection, providing actionable corrective suggestions to improve the development workflow.

This skill provides a comprehensive guide to configuring Hardware Security Modules (HSMs) using the industry-standard PKCS#11 interface. It details best practices for key generation, secure key storage, and cryptographic operations (signing, encryption, decryption). Learn how to manage keys in a tamper-resistant environment, ensuring private keys never leave the device boundary. Applicable for building compliance-grade security architectures across finance and government sectors.

This tool provides comprehensive security assessments for the entire IoT ecosystem, including physical hardware, embedded firmware, network communications, and cloud APIs. Testers can perform deep dives using hardware debugging (UART/JTAG), firmware extraction and reverse engineering, analyzing protocols (MQTT, CoAP, BLE), and simulating cloud-to-device attacks to identify vulnerabilities across all layers of the smart device stack.

This guide details establishing confidential computing environments using AWS Nitro Enclaves for hardware-level isolation. It covers building secure enclaves for sensitive data (PII, PHI), configuring cryptographic attestation workflows, and integrating KMS policies using PCR-based conditions. Learn to harden workloads by moving secret decryption into isolated, verifiable hardware boundaries.

A comprehensive guide for implementing phishing-resistant multi-factor authentication using FIDO2/WebAuthn protocols. Learn to build a complete relying party server using Python, supporting both roaming hardware keys (e.g., YubiKey) and platform biometrics. Covers registration ceremonies, credential storage, and migrating to passwordless authentication.

This skill provides advanced architectural guidelines for generating premium, award-level web experiences. It guides code generation beyond basic HTML/CSS, focusing on creating immersive digital environments. Key areas include sophisticated motion design (scroll-driven narratives, micro-interactions), establishing strong visual identities (e.g., Brutalism, Glassmorphism), and enforcing strict performance best practices like hardware acceleration and accessibility compliance.

Cirq is an open-source framework from Google Quantum AI used for designing, simulating, optimizing, and running quantum circuits. It supports NISQ circuit development, noise modeling, and compilation for various quantum hardware backends, including Google Quantum AI, IonQ, and AQT. It is essential for quantum algorithm research and hardware characterization.