This repository is a comprehensive collection of JavaScript interview questions and answers, serving as an educational resource for developers preparing for technical interviews. It consists of hundreds of questions organized by topic and difficulty, each with detailed explanations, code examples, and further reading references. The content is structured with metadata enabling categorization, filtering, and multilingual support (English, Portuguese, Chinese). The repository includes automated systems for generating the README from structured data, validating content quality, and managing translations. As a public mirror of GreatFrontEnd's main repository, it provides a searchable, well-organized knowledge base covering core JavaScript concepts, web APIs, security, performance optimization, testing, and design patterns.
This repo is a structured AI-assisted long-form article writing system, primarily delivered as a Claude Code plugin and a Tauri desktop app. It orchestrates a 14+ stage workflow (topic clarification, research, drafting, humanization, fact-checking, export) using specialized subagents and a central workflow contract (`collab_v2.json`). The system is model-agnostic, supporting Anthropic-compatible APIs including Chinese providers. It includes extensive tooling for evidence management, style modeling, blind evaluation, and publication metrics. While the core functionality is robust and well-tested, the codebase suffers from triple directory mirroring (`.claude/`, `claude-runtime/`, `plugins/writing-agent/`) requiring manual sync, hardcoded Windows paths in the desktop app, and a partially unverified style library. The architecture cleanly separates agent prompts (Markdown), runtime scripts (Python/Node), and a Tauri frontend, making the workflow itself reusable as a pattern for multi-stage AI agent orchestration.