Skill UI

A powerful CLI and API client for exploring the entire Go ecosystem. It queries pkg.go.dev to provide comprehensive documentation, API references, usage examples, available versions, dependency relationships, and known security vulnerabilities for any Go package or module. Ideal for developers conducting library research, checking compatibility, or auditing dependencies.

This skill enables comprehensive security graph mapping by ingesting both on-premises Active Directory data (via SharpHound) and cloud Entra ID data (via AzureHound) into BloodHound CE. It analyzes complex, hybrid attack paths, allowing security teams to identify critical privilege escalation chains from low-privileged accounts to Tier-0 assets, mapping findings to MITRE ATT&CK.

This skill guides the secure migration from classical cryptography (RSA, ECC) to quantum-resistant algorithms (PQC). It covers building a Cryptographic Bill of Materials (CBOM), identifying data at risk (HNDL), and deploying hybrid key exchange protocols like X25519MLKEM768 to ensure long-term data security against quantum threats.

This skill utilizes NVIDIA's open-source garak framework to conduct comprehensive red-teaming assessments on Large Language Models (LLMs). It tests for critical vulnerabilities such as prompt injection, jailbreaks, data leakage, and toxic content generation by sending thousands of adversarial probes. Ideal for pre-deployment security validation, API guardrail testing, and generating defensible evidence for AI risk assessments.

Trivy is an open-source, comprehensive scanner used to find vulnerabilities (CVEs), misconfigurations, secrets, and license issues across multiple targets. It is essential for implementing 'shift-left' security gates in CI/CD pipelines, scanning container images, Infrastructure-as-Code (IaC) like Terraform/Kubernetes, and generating/re-scanning SBOMs for supply chain transparency.

A comprehensive red-teaming skill for assessing the security posture of Retrieval-Augmented Generation (RAG) pipelines. It systematically probes two critical injection surfaces: poisoned retrieved context (indirect prompt injection) and embedding manipulation. Use this skill to validate retrieval guardrails, ensure data leak prevention, and demonstrate vulnerabilities in LLM-powered knowledge assistants.

A comprehensive skill for managing AWS operational excellence, cost governance, and observability. It provides guidance on pre-deployment cost estimation (TCO), detailed spending analysis using Cost Explorer, setup of CloudWatch alarms, auditing activity via CloudTrail, and overall security posture assessment. Essential for optimizing cloud spending and ensuring reliable infrastructure.

This guide provides a comprehensive reference and usage guide for the Redis Command Line Interface (redis-cli). It covers connecting, executing commands in different modes, and offers detailed cheat sheets for all core Redis data structures (Strings, Hashes, Lists, Sets, Sorted Sets). Crucially, it also includes important security considerations and best practices, ensuring users can manage and troubleshoot Redis databases safely from the command line.

This skill performs a comprehensive, read-only, multi-agent review of a git diff or file scope. It launches four specialized sub-agents—covering Regression, Security, Performance, and Contracts—in parallel. The main agent then aggregates, filters, and summarizes critical findings, ensuring the code change is robust, secure, and maintainable. Ideal for pre-commit or Pull Request review workflows.

Run comprehensive, read-only exposure checks against your local machine or project directories in response to security advisories and CVEs. This tool systematically checks various ecosystems (Node.js, Python, Homebrew, etc.) to generate a structured, non-invasive audit report, helping users understand their actual risk exposure without making any system changes.

This comprehensive guide outlines a rigorous, human-in-the-loop engineering workflow for leveraging advanced AI agents to complete complex implementation tasks. It mandates defining clear completion criteria, decomposing work into manageable units, and strategically routing models (Haiku, Sonnet, Opus) based on task complexity. The workflow emphasizes continuous evaluation, regression testing, security review of invariants and edge cases, and strict cost discipline to ensure robust and reliable software development using AI assistance.

Use CronCreate to schedule background workers that must persist even after session restarts. This utility provides various recommended schedules for critical, recurring tasks like security audits, performance optimization, memory consolidation, and documentation generation. It is essential for CI/CD pipelines, continuous monitoring, and maintaining system health.