Skill UI

An advanced debugging skill designed for AI agents. It utilizes gdb-cli to provide intelligent assistance for C/C++ programs, enabling the analysis of core dumps, debugging live processes, and investigating complex issues like crashes, deadlocks, and memory corruption. It correlates runtime state inspection with source code context for deeper insights.

This skill enables AI assistants to interact with the Hugging Face Hub via Model Context Protocol (MCP). Users can search for models, datasets, and papers, retrieve repository details, fetch documentation, and execute compute jobs on GPU or CPU. It also allows leveraging Gradio Spaces as functional AI tools. Ideal for developers and researchers needing direct access to the HF ecosystem for model discovery, training, and deployment workflows.

An ethical HR assistant for hiring, onboarding, performance management, and policy compliance. It generates job descriptions, interview kits, and checklists while adhering to labor laws and privacy standards. Ideal for HR professionals needing compliant workflows and documentation.

Draft internal communications including 3P updates, company newsletters, FAQ responses, status reports, and leadership updates from approved sources.

A comprehensive index of 46 production-grade test automation skills, covering E2E, unit, mobile, BDD, and cloud testing across 15+ languages. This skill equips AI coding assistants to act as senior QA architects, generating structured, real-world test code for major frameworks like Playwright, Selenium, Cypress, and Jest. It supports project setup, CI/CD integration, and cross-platform debugging.

This skill guides users through the entire lifecycle of developing intelligent AI assistants, chatbots, and conversational interfaces. It specializes in establishing robust natural language understanding, managing multi-turn context, and defining best practices for creating seamless, production-ready AI applications with real-world value.

This skill acts as a literature-research assistant, orchestrating a Python CLI to interface with APIs like Semantic Scholar and arXiv. It enables users to search for academic papers by topic, retrieve detailed metadata, perform impact analysis using citation tracking, download PDFs, and extract text content. It streamlines the entire academic research workflow from initial discovery to deep reading.

This blueprint guides the creation of F.R.I.D.A.Y., a tactical, low-latency voice assistant inspired by Iron Man. It utilizes the specialized Pipecat framework to orchestrate a comprehensive, real-time audio pipeline: STT (OpenAI Whisper/GPT-4o) -> LLM (Gemini) -> TTS (OpenAI Nova). Ideal for developers needing to build advanced, multi-provider, conversational voice applications.

Proofreads and corrects grammar, spelling, punctuation, clarity, and tone while preserving the author's voice. Supports inline text and file processing modes, returning corrected text with a modification log or saving an updated file with 'UPDATED_' prefix.

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability. This skill covers few-shot learning, chain-of-thought prompting, prompt optimization, template systems, and system prompt design. It helps in designing complex prompts for production applications, optimizing consistency, and debugging inconsistent outputs. Ideal for developers building AI assistants and production-grade LLM applications.

This skill guides users through software setup or installation processes step by step. It displays the current action and lists remaining steps to prevent overwhelm. The assistant ensures all prerequisites are met and updates the checklist dynamically. Ideal for complex configurations requiring clear, atomic instructions.

Launches an RSVP speed reader to display text one word at a time with Spritz-style highlighting. Useful for quick reading of provided text or assistant responses without document transformation.