Skill UI

Runs a comprehensive security scan on a live, deployed Power Pages site. It analyzes the site's public surface for vulnerabilities, fetching the latest report and providing a plain-language summary of findings, categorized by severity. Ideal for auditing, testing, or assessing the safety of a production environment.

This skill analyzes code for language and framework-specific security best practices. It is designed to help users write secure-by-default code, passively detect major vulnerabilities, or generate comprehensive, prioritized vulnerability reports. Supports languages including Python, JavaScript/TypeScript, and Go, ensuring robust security standards throughout the development lifecycle.

This comprehensive guide outlines the principles, architecture, and best practices for developing specialized, modular skills that extend large language model capabilities. Learn how to integrate domain expertise, multi-step workflows, API tool integrations, and structured resources while managing the context window efficiently.

This tool acts as a personalized mentor for Swedish language learners. It guides users by assessing their CEFR level and recommending curated, skill-specific resources (YouTube clips, podcasts) and a structured learning path for listening, reading, writing, and speaking. It prioritizes authentic, level-appropriate content from trusted sources.

Provides domain knowledge for compiling character/scene/prop creative settings into executable image generation prompts. Covers reference board layouts (character identity boards, sequence keyframes, environment study boards, prop study boards), composition and camera language, avoiding image moderation false positives, entity continuity, and cross-variant derivative design based on the main image. Not for video prompt compilation, pure material editing, or evaluating generated outputs.

Apply Eric Evans-inspired Domain-Driven Design rules for modeling complex domains. Define bounded contexts, protect ubiquitous language, and design aggregates. Use this skill for strategic domain modeling, context mapping, repositories, and domain services before making design or code decisions.

EarDraft transforms reading-oriented prose into listening-optimized text for flat, neutral vocal delivery (TTS, podcasts, audiobooks, CLE audio). It handles legal materials by expanding citations, symbols, and footnotes, and supports multiple languages and output formats including plain text, ElevenLabs tags, and SSML for Amazon Polly, Google Cloud TTS, and Azure.

Searches 153 adapters across 122 jurisdictions for foreign extradition and surrender decisions, each in its own language. Localises the requesting state's name per jurisdiction, gates hits for relevance, and saves dated reports for comparative extradition research. Leads, not authorities.

Design, implement, review, or refactor native macOS 27 Golden Gate interfaces in SwiftUI or AppKit. Ensures apps match Apple's current macOS 27 UI kit with restrained Liquid Glass language, integrated windows, full-height sidebars, native toolbars, flat lists, and clear pane boundaries. Ideal for Figma design-to-code work and audits of boxed interfaces.

Autonomous DevSecOps & FinOps guardrails that review Linux kernel patches for memory safety, analyze Terraform cost drifts to prevent bill spikes, and translate natural language security intent into hardened Kubernetes policies. Integrates advanced AI reasoning into the SDLC for high-stakes audits and CI/CD quality gating.

This skill helps secure Large Language Model (LLM) and AI deployments against various threats including prompt injection, data exfiltration, model theft, and supply chain attacks. It covers implementing guardrails, output filtering, PII scrubbing, and API security measures to ensure compliance with standards like SOC2 or ISO 27001.

A set of behavioral guidelines derived from Andrej Karpathy's observations to help users writing, reviewing, or refactoring code with Large Language Models (LLMs). It guides developers to avoid overcomplication, make surgical changes, explicitly surface assumptions, and define verifiable success criteria, promoting clean, simple, and robust code development.