Skill UI

This skill facilitates an interactive Quality Assurance (QA) session. Users can conversationally describe encountered bugs or issues. The agent clarifies the problem, explores the codebase for context and domain language, and then meticulously files durable GitHub issues. It supports both single-issue reports and breaking down complex problems into multiple, independently verifiable tickets, ensuring developers receive actionable, high-quality reports written from the user's perspective.

Qdrant is a high-performance vector database. This client SDK suite provides official, easy-to-use libraries for multiple programming languages (including Python, Java, Go, and TypeScript). It enables developers to seamlessly integrate sophisticated vector search capabilities into their applications, supporting both REST and gRPC APIs. Ideal for building semantic search engines, recommendation systems, and advanced AI applications.

This comprehensive benchmark suite evaluates the performance of Vision-Language Models (VLM) on complex video anomaly detection tasks using the SmartHome-Bench dataset. It covers a wide range of real-world smart home scenarios, including security breaches, elderly fall detection, and unusual pet behavior. Unlike single-frame analysis, this benchmark requires deep multi-frame video understanding, making it a robust tool for testing the advanced AI capabilities of video monitoring systems.

An expert guide covering advanced exploitation techniques for Expression Language (EL) injection across multiple Java frameworks, including Spring (SpEL), Struts2 (OGNL), and JSP/JSF (Java EL). Details detection methods, sandbox bypasses, and real-world CVE chains for Remote Code Execution (RCE).

This tool searches a comprehensive database of over 2500 curated open-source repositories for tools related to Large Language Models (LLMs), ChatGPT, RAG, agents, and NLP. It interprets natural language queries, converts non-English inputs to core English keywords, and systematically filters results across multiple specialized categories (e.g., LangChain, Chatbots, CLIs). Use it whenever the user needs to find specific AI development libraries or open-source AI tooling.

A powerful skill that enables natural-language interaction with complex DeFi protocols across multiple EVM chains. It acts as a non-custodial agent, interpreting user prompts (e.g., 'swap X for Y') into simulated, multi-step transactions (like approve + swap). It utilizes account abstraction (EIP-7702/ERC-4337) to simulate and queue secure, user-signed transactions via the CLI, making advanced DeFi accessible from the terminal.

Flox is a declarative, Nix-based environment manager designed to create perfectly reproducible development environments. It handles system-level dependencies (like compilers, databases, and native libraries) and ensures that complex toolchains across multiple languages (Python, Node.js, Go, etc.) function identically across macOS and Linux. Ideal for solving 'works on my machine' issues and onboarding new team members instantly.

This skill automatically generates comprehensive unit tests based on provided source code. It supports multiple programming languages (Python, JavaScript, Java, Go, Rust) and popular testing frameworks (pytest, Jest, JUnit). Use it to improve code coverage, test boundary conditions, and validate error handling efficiently, saving manual testing time.

This skill facilitates professional multilingual dubbing for local audio and video assets. Users can submit source media for translation and dubbing into various target languages and locales. It manages the entire workflow—from job submission and status polling to final artifact download—while enforcing critical checks for source rights, speaker consent, and appropriate regional accents.

jscpd is a comprehensive code quality tool designed to detect copy-pasted or duplicated segments across programming source code. Supporting over 150 languages, it identifies redundant code blocks and calculates the overall duplication percentage. It offers multiple reporters (AI, HTML, JSON) and integrates with refactoring workflows to help developers maintain high code integrity.

This skill implements the LLM Council concept, enabling multiple open-weight language models to collaborate on complex queries. The process follows a three-stage deliberation: 1) Parallel independent responses from selected models; 2) Peer-to-peer ranking of the responses; and 3) Final synthesis by a designated Chairman LLM. Powered by Fireworks AI, it ensures deep, multi-faceted analysis and consensus building for high-stakes decision support.

This skill outlines the implementation of advanced runtime defenses for production Large Language Model (LLM) applications. It covers using multiple industry-leading guardrail systems—including Llama Guard, NeMo Guardrails, and LLM Guard—to detect and block adversarial attacks such as prompt injection, jailbreaks, and toxic content. It provides a comprehensive defense-in-depth strategy for ensuring model safety and output integrity in real-world deployments.