Skill UI

LiteParse is a fast, open-source, and local document parser designed for layout-aware text extraction from PDFs, images, and office files. It outputs structured JSON with bounding boxes and metadata, making it ideal for building advanced RAG systems, citation grounding, and complex data pipelines without needing cloud APIs. Features include OCR, batch processing, and page screenshot capture.

This skill guides the design of robust, production-grade data extraction pipelines, moving beyond brittle one-off scripts. It supports three modes: API-driven web scraping (Firecrawl), traditional local Python extraction (PDF, CSV), and hybrid workflows. Key features include intelligent routing, mandatory data validation, secure key management, and adherence to scraping best practices.

This skill captures and persists critical user decisions, project constraints, and architectural choices across multiple sessions and agents. It saves this context into a structured memory database (`mdbase`), ensuring that future development steps or agents can retrieve the original intent without re-deriving it from scratch. Ideal for documenting project rules, tech stacks, and design rationale.

A comprehensive, multi-phase quality assurance tool designed for Next.js fullstack applications. It verifies production readiness by checking code integrity, build success, SEO metadata, API authentication, route stability, performance, and security vulnerabilities. Use it as a mandatory pre-deployment checklist before promoting an app to production.

A powerful tool for designing and writing deterministic, multi-agent workflow scripts in JavaScript. It allows users to orchestrate complex, repeatable, multi-step tasks using advanced patterns like fan-out, pipelines, loops, and judge-panels. Ideal for automating sophisticated business processes that require multiple specialized sub-agents and robust context management.

Converts complex, long-form markdown (like RFCs, specs, or reports) into a single, polished, and lightly interactive HTML file. It features a sticky Table of Contents, search functionality, advanced code-copy buttons, and integrates with design systems for professional branding, all without needing a build step or framework runtime.

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.

This skill is designed to prevent AI coding assistants from exhibiting sycophantic agreement bias. When active, it forces a structured, critical assessment of user claims. The process involves extracting the core claim, assessing it independently with evidence (for/against), and concluding solely based on that assessment, ensuring objective and evidence-based responses.

HasData is a comprehensive cloud platform designed for extracting structured public web data. It supports three core execution modes: Web Scraping API for arbitrary URLs (including JS rendering), pre-parsed Scraper APIs for known platforms (like Google or Amazon), and asynchronous Scraper Jobs for bulk or recursive crawling. Ideal for market research, e-commerce intelligence, job data collection, and local business lead generation.

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.

Open Dynamic Workflows (ODW) is an advanced, open-source engine designed to manage complex coding tasks using multiple AI agents. It operates in three stages: planning the task into parallel subtasks, orchestrating various coding agents (like Codex or Antigravity) to work concurrently, and finally, performing an adversarial verification pass to challenge and validate the combined output before merging. It supports multiple model providers and is ideal for structured, high-reliability software development.