Skill UI

This skill provides a structured workflow for porting existing Semgrep security rules to multiple target languages. It guides users through applicability analysis, test-first rule creation, and validation for each language variant, ensuring consistent and accurate security coverage across polyglot codebases.

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.

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 skill provides methods for reliably extracting typed, validated, and structured data from Large Language Models (LLMs), moving beyond simple text parsing. It covers best practices across major APIs (OpenAI's response_format, Anthropic's tool_use, Google's responseSchema) and local models. Key workflows include defining schemas (Pydantic/Zod), implementing constrained decoding, and building robust retry loops for production-grade data pipelines.

This utility provides a comprehensive framework for proactive threat hunting, focusing on detecting advanced and suspicious PowerShell execution patterns. It covers common attacker techniques such as encoded command usage, download cradles (IEX), AMSI bypass attempts, and constrained language mode evasion. It is designed for security analysts during incident response and threat intelligence validation, requiring EDR and SIEM telemetry.

A comprehensive guide for authorized penetration testers on identifying and exploiting insecure deserialization vulnerabilities across multiple languages (Java, PHP, Python, .NET). Covers techniques for generating payloads using tools like ysoserial and phpggc, and testing various application components such as cookies, HTTP parameters, and message queues to achieve potential Remote Code Execution (RCE).

This guide details how to use Google Distroless images to drastically reduce the attack surface of containerized applications. By eliminating shells, package managers, and unnecessary OS utilities, these minimal base images enhance security, align with compliance standards, and improve supply chain security in Kubernetes and Docker deployments. It provides multi-stage build patterns for various languages (Go, Java, Python, Node.js).

This file serves as the dedicated translation resource for the MCP Server Patterns library. It is used to localize key strings and texts to ensure accurate user experience across different languages. Developers should refer to the original skill file for the core English content.

A comprehensive guide for mastering version control using GitHub and Git. It provides two modes: Guided Setup for first-time users, and an adaptive, hands-on curriculum for learning advanced concepts like branching, PR workflows, and CI/CD. The system automatically adjusts language and depth based on the user's skill level, ensuring effective, real-world learning.

AegisOps-AI is a professional-grade 'Living Pipeline' that integrates advanced AI reasoning directly into the SDLC. It acts as an intelligent gatekeeper, automating high-stakes audits across three domains: identifying memory vulnerabilities in Linux Kernel patches, detecting massive cost drifts in Terraform plans, and translating natural language security intent into hardened Kubernetes manifests.

A powerful operational companion for database developers. This skill assists with the daily lifecycle of database interactions, including translating natural language requirements into optimized SQL queries, generating database migrations, performing comprehensive schema introspection across multiple dialects (PostgreSQL, MySQL, SQLite, SQL Server), and identifying performance bottlenecks through detailed query optimization and index recommendations. It also supports ORM patterns like Prisma and SQLAlchemy.

This skill guides developers on building LLM-powered applications using the Claude API, Anthropic SDKs, or the Agent SDK. It provides comprehensive guidance on language detection, best practices (like default model versions and streaming), and choosing the correct development surface (API call, Workflow, or Agent) based on the use case.