SkIDEancer - The New Fuse Cloud IDE

AI-powered Cloud IDE for The New Fuse platform. Full coding experience with integrated AI assistants, code analysis, and MCP tool support.

Features

🤖 AI Integrations

• Anthropic Claude - Advanced reasoning and code generation
• OpenAI GPT - GPT-4 and GPT-4.1 turbo support
• Ollama - Local model support for offline development
• HuggingFace - Open-source model access
• AI Chat Interface - Unified chat for all AI providers

💻 Development Features

• Monaco Editor - VSCode-quality editing experience
• VSCode Extension Compatibility - Install extensions from Open VSX
• Integrated Terminal - Full terminal with AI assistance
• Git Integration - Full git support with visual diff
• Search - Workspace-wide semantic search
• Debug - Debug adapter protocol support

🔌 TNF Ecosystem Integration

• MCP Integration - Model Context Protocol for AI tools
• SkIDEancer Coder - Built-in AI coding assistant
• Code Analysis - AI-powered security scanning and metrics
• Flow Orchestration - Automated development workflows

Quick Start

Local Development

# Install dependencies (requires Yarn)
yarn install

# Start development server
yarn dev

# Production start
yarn start

Environment Variables

# AI Provider API Keys
OPENAI_API_KEY=sk-...
ANTHROPIC_API_KEY=sk-ant-...
HUGGINGFACE_API_KEY=hf_...

# Ollama (if using local models)
OLLAMA_HOST=http://localhost:11434

# TNF Integration
CLOUD_SANDBOX_URL=https://tnf-cloud-sandbox-production.up.railway.app
CLOUD_SANDBOX_WS=wss://tnf-cloud-sandbox-production.up.railway.app/ws

# Server
PORT=3007

Railway Deployment

This repository is configured for Railway deployment:

1. Connect this repo to Railway
2. Set environment variables
3. Deploy

The Dockerfile handles everything.

Architecture

skideancer-ide/
├── src-gen/
│   ├── backend/
│   │   └── main.js         # Server entry point
│   └── frontend/
│       └── index.html      # Frontend entry
├── lib/                    # Compiled modules
├── static/
│   └── branding/           # SkIDEancer branding assets
├── packages/
│   └── skideancer-ai-agent/ # Custom AI agent package
├── plugins/                # VSCode-compatible plugins
├── defaults/
│   └── preferences.json    # Default IDE preferences
├── Dockerfile              # Railway deployment
└── package.json            # Dependencies

Integration with TNF Ecosystem

SkIDEancer is part of The New Fuse platform:

• Main Monorepo: whodaniel/fuse (pnpm)
• SkIDEancer: This repository (yarn)
• Cloud Sandbox: MCP tools server

Why Separate Repository?

The underlying framework requires Yarn while the main monorepo uses pnpm. Separating ensures:

• Clean dependency management
• Independent deployment pipelines
• Faster CI/CD builds

Troubleshooting

502 Bad Gateway on Railway

Symptoms: Deployment shows "success" but accessing the URL returns 502 Bad Gateway.

Solutions:

1. Start command - Ensure Railway uses:

   node src-gen/backend/main.js --hostname 0.0.0.0 --port $PORT

2. Port binding - The app must bind to 0.0.0.0, not localhost

"The configuration is not set" Error

Symptom: Console shows Error: The configuration is not set

Solution: The Dockerfile includes automatic patching. If building locally, ensure the three-phase patch runs during build.

Slow Startup Warnings

DefaultMessagingService.initialize took longer than expected warnings are normal. The backend is fully functional despite these warnings.

Version

• SkIDEancer: v13 (2025-12-25)
• Node.js: 22 (via Dockerfile)
• MCP SDK: 1.16.0

Changelog

v13 (2025-12-25)

• Full SkIDEancer rebranding - Removed legacy naming throughout
• Custom Deep Space theme - TNF brand colors
• Welcome page - New branded welcome experience
• AI feature prominence - Highlighted AI capabilities

v12 (2025-12-25)

• Fixed 502 Bad Gateway with correct production entry point
• Added three-phase config patching
• Comprehensive troubleshooting docs

v11

• Initial startup command fix

v10

• Initial Symbol.for patch

License

MIT - Part of The New Fuse project

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