Skill UI

This skill interviews users to extract project vision, decisions, and preferences into durable documentation like README and ADRs. It follows a structured loop: checking existing docs, asking varied questions, and updating documents after every answer. The goal is to save user judgment and knowledge into clear markdown files. It ensures consistency and captures the project's core identity through back-and-forth interaction.

This skill guides you through a comprehensive, multi-phase interview to capture every necessary detail of a new project idea. It is designed to run BEFORE any code is written, forcing detailed specification gathering across purpose, features, data models, and technical constraints. The output is a clean, self-contained prompt.md file, ensuring subsequent development is based on solid, unambiguous requirements and preventing costly mistakes.

BrowserAct is a browser automation CLI for AI agents, enabling real browser interaction, JavaScript-rendered extraction, screenshots, network capture, parallel sessions, verification handling, and human handoff. Ideal for tasks requiring authenticated state, dynamic content, or multi-session isolation.

This skill transforms completed debugging sessions or repeated corrections into evidence-backed procedures. It captures reusable lessons upon explicit request, ensuring privacy by not automatically saving memories. Users must provide session summaries or transcripts to identify failures and verify fixes. The output is a reviewed procedure suitable for documentation, excluding secrets and personal details. It helps maintain knowledge without modifying agent configuration automatically.

This skill facilitates structured, bidirectional reading and knowledge synthesis for academic texts, theories, and articles. It forces users to first capture the source material's original intent, before critically mapping its relationships, conflicts, and absorptions against the CrossFrame framework. It ensures structured output with clear source boundaries, making it ideal for deep learning and scholarly work.

A comprehensive style guide for implementing the Cyber Y2K aesthetic across web and mobile applications. This design package captures the retro-futuristic blend of late 90s/early 2000s digital culture, modern glitch art, and iridescent holographic gradients. It provides detailed code examples using CSS, SwiftUI, and Flutter to achieve key effects like RGB splitting, animated gradients, and aggressive vector typography.

This skill enables the creation of comprehensive monitoring solutions for database migrations. It covers Change Data Capture (CDC) pipelines, real-time data synchronization, anomaly detection, and automated alerting. You will learn to build observability infrastructure using tools like Prometheus, Grafana, Kafka, and Debezium to track migration metrics, document processing, and replication lag in enterprise environments.

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 agent automates iOS app debugging on a booted simulator using XcodeBuildMCP. It handles project building, running, UI interaction, screenshot capture, and log monitoring. Ideal for testing and inspecting app behavior during development cycles without manual intervention.

A powerful command-line tool for recording the macOS screen and capturing system audio simultaneously. Unlike QuickTime or standard `screencapture`, this tool captures raw display and system audio directly via ScreenCaptureKit, eliminating the need for complex virtual audio drivers (like BlackHole) or elevated permissions. It is designed for scripted content creation, automated demos, and complex recording scenarios where system audio is required via the CLI.

Use Mailtrap Email Sandbox to capture and inspect outbound emails without sending them to real recipients. This is crucial for development, staging, and CI/CD environments. It allows developers to test email content, headers, attachments, and spam scores using dedicated APIs, SMTP settings, or SDKs, ensuring mail integrity before deployment. Ideal for automation and rigorous quality checks.

Maintain a review-first engineering wiki with provenance, citation-aware queries, explicit capture and promotion, and deterministic checks. Helps teams capture durable lessons and verify knowledge before turning it into rules.