Skill UI

This central skill specializes in performing comprehensive threat modeling using STRIDE and calculating risk via DREAD scoring. It guides users through defining scope, identifying threats, and planning mitigations for new architectures. Crucially, it acts as a security router, directing specialized requests—such as pen-testing, incident response, cloud posture checks, and AI security reviews—to the appropriate dedicated skill.

This skill provides a comprehensive framework for the continuous self-improvement of makepad-skills. It outlines automatic skill triggering via hooks, context-aware skill routing, and a structured process for capturing new patterns, error solutions, and best practices. It ensures the entire skill library remains robust and up-to-date throughout the development lifecycle.

This skill guides the development of EarLLM One, a complex Android application. The app captures real-time audio from Bluetooth earbuds, transcribes the voice using STT, sends the text input to a Large Language Model (LLM) via a robust pipeline, and plays the response back using TTS. It requires deep knowledge of Kotlin, Android development, Bluetooth profiles (A2DP/HFP), and advanced audio routing.

This powerful orchestrator coordinates the entire product development lifecycle by routing inquiries across 16 specialized sub-skills (e.g., RICE, OKRs, UX research, analytics). It acts as a central hub for both deterministic task routing and running continuous, machine-gated discovery loops. Use it when you need to systematically prioritize features, run A/B tests, or drive a goal from initial assumption to validated repository code.

This skill guides the setup of a robust, centralized logging pipeline using Fluent Bit and Fluentd. It covers collecting logs from diverse sources (syslog, files, applications), routing, filtering, and enriching them before sending them to destinations like Elasticsearch, S3, or Splunk. Ideal for centralizing observability and building secure logging architectures across distributed infrastructure.

This skill guides comprehensive security testing for Host Header Injection vulnerabilities in web applications. It simulates attacks to identify critical risks such as password reset poisoning, web cache poisoning, Server-Side Request Forgery (SSRF), and virtual host routing manipulation. It is essential for penetration testers assessing backend security behind proxies and load balancers.

SvelteKit is the official full-stack framework built on Svelte, enabling developers to build fast, modern, and highly performant web applications. It provides comprehensive features including file-based routing, Server-Side Rendering (SSR), Static Site Generation (SSG), API routes, and progressive form actions, all while maintaining Svelte's zero runtime overhead. Use this skill when building complex, data-driven web platforms where performance and developer experience are paramount.

A comprehensive knowledge-base-first skill designed for deep literature reviews in advanced communication domains. Use it for topics like 4G/5G/6G, wireless networking, satellite communications, Wi-Fi, routing protocols, and cross-layer optimization. It systematically searches structured academic databases (IEEE, ACM, Zotero, etc.) to provide related work, survey papers, and landscape summaries.

Design and implement a unified operational workflow for managing notifications sourced from disparate tools like GitHub, Linear, local hooks, and chat platforms. This skill addresses notification fragmentation, alert noise, and redundancy by establishing clear severity levels, ownership, routing channels, and next operational actions into a single, cohesive pipeline.

This skill ensures code implementation is grounded in official documentation rather than memory or outdated training data. It verifies framework-specific patterns, APIs, and best practices against authoritative sources before coding. Ideal for building reliable boilerplate, handling framework features like routing or state management, and ensuring correctness in version-sensitive environments. Every pattern is cited with its source.

A comprehensive guide to advanced, production-ready LLM inference using LangChain 1.0. This skill addresses common pitfalls and bugs when integrating multiple providers (Claude, GPT-4o, Gemini), covering issues like structured output reliability, correct streaming token accounting, and robust handling of complex AIMessage content blocks. It teaches best practices for model initialization, provider routing, and version-safe code implementation.

This internal agent skill automates the complex process of determining the most likely owner or team for a bug cluster. It follows a strict 6-level precedence model, starting with cached overrides, and sequentially querying sources like Service Owners, Oncall status, CODEOWNERS, recent assignees, and committers. The process includes staleness detection and confidence scoring, providing highly accurate and auditable routing recommendations for internal development triage.