Skill UI

This guide provides best practices for building flexible, maintainable, and scalable React components. It emphasizes using composition patterns and compound components to avoid 'boolean prop proliferation,' while also detailing advanced concepts in component architecture, state management, and modern implementation techniques (including React 19 APIs). Ideal for refactoring complex systems or designing reusable component libraries.

A comprehensive, AI-powered suite designed to generate high-quality, platform-optimized content for LinkedIn. It creates full posts, multi-slide carousels, long-form newsletters, and 30-day content calendars. The tool integrates niche-specific SEO rules and features a reinforcement-learning memory system, ensuring that your content style and performance improve with every piece of feedback.

This deployment skill is designed to be integrated into the Playwright testing workflow. Its primary function is to validate the loading process of shared skills across the entire environment during the startup phase. It ensures that all necessary components and modules are correctly registered and available for reliable End-to-End (E2E) testing execution.

Creates academic conference posters (ICML/NeurIPS/ICLR/CVPR) as single HTML/CSS files with hard measurement gates, real paper figures, two-hue design tokens, and print-ready PDF via headless Chromium.

This skill provides a direct shell call to capture the current Git diff (staged, working-tree, or specific file list) as raw text. It is designed for workflows requiring repository diffs without the overhead of an LLM agent loop, offering significant performance improvements over traditional sub-agent calls.

A lightweight utility designed for fetching content from a single URL via HTTP or HTTPS. It supports various methods (GET, POST, PUT, DELETE) and allows configuration of timeouts and maximum response body sizes. This tool is ideal for quick, simple data extraction steps within a workflow DAG, offering significant performance gains over complex LLM agent loops. Note that complex tasks like JS rendering or multi-page crawling require dedicated sub-agents.

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 meta-skill is designed for generating comprehensive competitive intelligence briefs for sales, business development, and strategy teams. It monitors signals across various dimensions (pricing, product, leadership, funding, etc.) for specified competitors or targets over a defined time window. It helps track changes against a baseline and provides actionable recommendations, moving beyond simple raw data dumps.

This meta-skill acts as a watchdog for long-running processes, such as CI image builds or overnight model fine-tunes. It utilizes a sub-agent to continuously monitor the output via tmux, automatically diagnose failures, propose corrective fixes, and persist the entire resolution process to memory. It is designed for robust, automated debugging of complex system tasks.

This meta-skill is designed to orchestrate the creation of complex, multi-step workflows (meta-skills). It should only be used when a user explicitly requests combining, synthesizing, or proposing a new skill that coordinates multiple existing functions. The process includes intent clarification, trigger collision checking, validation, and generating a detailed proposal containing the workflow DAG.

This meta-skill is designed to automate the diagnosis of complex programming errors. When presented with a stack trace, traceback, or failing log, it orchestrates a multi-step investigation. It parses the trace, searches the repository history, checks relevant issues, and analyzes code diffs to provide a comprehensive brief for root cause analysis and debugging.

A comprehensive workflow designed to convert unstructured conversational data, meeting notes, and ad-hoc decisions into highly structured, linkable entries within Notion. This tool ensures that all captured knowledge—whether an FAQ, a 'how-to' guide, or a formal decision log—is properly documented, categorized, and linked to maintain a cohesive, searchable knowledge base for easy reuse across teams.