Skill UI

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.

An expert guide for deploying and optimizing Large Language Models (LLMs) entirely on local hardware. Mastering the entire local AI ecosystem, including inference engines like Ollama, vLLM, and llama.cpp. Provides deep knowledge on quantization formats (GGUF, EXL2, AWQ), VRAM calculation, and ensuring privacy-first, offline deployment for state-of-the-art models.

Guide for configuring Hardware Security Modules with the PKCS#11 interface to generate, manage, and operate on keys securely, covering SoftHSM2 development setups and cloud HSM integrations for compliance and hardened deployments.

Guide for integrating Hardware Security Modules via PKCS#11—covering slot/token discovery, key creation, signing, verification, and compliance reporting with python-pkcs11, AWS CloudHSM, and YubiHSM2 in security assessments or audits.

Performs comprehensive IoT device security assessments, combining hardware interface testing, firmware extraction, runtime exploitation, and network/cloud/mobile analysis to find vulnerabilities before deployment or for product reviews.

This skill is designed for performing local, on-premise evaluations and benchmarking of models hosted on the Hugging Face Hub. It facilitates running specialized evaluation frameworks like `inspect-ai` and `lighteval` against local hardware. Users can select optimal inference backends, including `vllm` for high throughput, or fall back to Hugging Face Transformers or `accelerate`, ensuring comprehensive smoke testing and task selection for LLMs. It focuses purely on the local execution process, separate from remote jobs or publishing workflows.

Implements end-to-end FIDO2/WebAuthn hardware security key authentication, covering server configuration, registration and authentication ceremonies, YubiKey enrollment, and passkey migration so high-value accounts gain phishing-resistant, passwordless MFA.

This skill provides a comprehensive framework for validating the integrity and recoverability of critical data backups. It goes beyond simple file checks by implementing cryptographic hash verification (SHA-256), simulating automated restore tests in isolated environments, detecting silent data corruption (bit rot), and scanning for signs of ransomware artifacts. It is crucial for ensuring data reliability against cyberattacks and hardware failures, adhering to standards like NIST CSF.

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 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.

Hardware-agnostic quantum ML framework enabling gradient-based training of quantum circuits, hybrid quantum-classical models, and seamless integration with PyTorch/JAX/TensorFlow alongside device portability across IBM/Google/Rigetti/IonQ.