Skill UI

This template simulates a hand-drawn, low-fidelity wireframe session on a whiteboard or sketchpad. It includes graph paper backgrounds, marker scribbles, sticky notes, and multiple tabs, making it ideal for early-stage UI/UX brainstorming and capturing initial conceptual ideas.

An interactive skill designed to interview users to capture project vision, core decisions, and technical preferences. It systematically converts raw discussions into structured documentation, maintaining the project's history in ADRs (Architectural Decision Records) and its overarching goal in the README.

This skill utilizes the Taisly Agent Kit to manage the entire workflow for publishing approved short-form videos across major platforms, including TikTok, Instagram Reels, YouTube Shorts, X, and Facebook. It facilitates agent-assisted publishing by ensuring coordination of captions, metadata, and campaign details. A critical feature is the mandatory explicit confirmation gate, which prevents any state-changing publishing action without explicit user approval, prioritizing safety and compliance.

This advanced trading journal captures the full context of a trade, recording not only the fill price and P&L, but also the initial thesis, the defined plan (stop/target), and the emotional state at the time of entry. It integrates with Notion to log and review trades, grading the quality of decisions and execution against the user's own plan, ensuring users learn from process, not just profit.

This skill fetches raw text transcripts from any YouTube video. It prioritizes using the DeepAPI service for reliable, server-side scraping, which bypasses local bot detection issues. If DeepAPI fails or the API key is unavailable, it gracefully falls back to using the local `yt-dlp` tool. The output is always saved as a clean, unformatted .txt file.

This skill provides a systematic, four-phase workflow for diagnosing and recovering from AI agent failures. It guides the agent to first capture the failure state, diagnose the root cause (e.g., loop, context overflow, state drift), apply minimal containment recovery actions, and finally generate a detailed introspection report, minimizing the need for human intervention.

This skill helps developers structure and record critical architectural decisions (ADRs) made during coding sessions. It automatically detects moments of decision, capturing the context, alternatives considered, and the rationale (trade-offs and consequences). This maintains a living log that explains 'why' the code base was built the way it is, preventing knowledge loss and improving project maintainability.

This skill drives a complete authentication flow for a target website, handling credentials and multi-factor authentication (MFA). Critically, it sanitizes all captured cookies using AIDefence and stores only an opaque vault handle in a dedicated memory store. This allows downstream skills to reuse the authenticated session without requiring the user to re-login, making it ideal for persistent agent operations.

This primitive skill initiates and manages a named, traceable browser session. It captures every user action, state change, and snapshot into a structured RVF cognitive container. This mechanism is essential for complex, multi-step web interactions, allowing downstream skills to reliably compose, replay, and analyze the entire browsing journey.

A comprehensive guide to building highly performant and reusable UIs across multiple platforms (Android, iOS, Desktop, Web) using Compose Multiplatform and Jetpack Compose. It details advanced patterns for state management (Single State Object, Event Sink), type-safe navigation, slot-based composables, platform adaptation (Expect/Actual), and crucial performance optimization techniques.

This system generates platform-native content for multiple channels, including X, LinkedIn, YouTube, and newsletters. It operates on a source-first workflow, ensuring that the author's unique voice and core ideas are preserved while adapting the content to the specific formatting and best practices of each target platform.

This skill analyzes completed code sessions to automatically extract reusable patterns, transforming raw interaction data into structured, learned skills. It allows the AI to continuously improve its domain knowledge by capturing techniques like error resolution, debugging methods, and workarounds, making it effective for advanced coding assistance and knowledge curation.