Reliable Shiny Code with Copilot and Posit’s VS Code Extension

If you've tried using GitHub Copilot or other LLM-based coding assistants with Shiny, you've likely experienced frustration. Despite their impressive capabilities with mainstream languages, these tools frequently hallucinate when generating Shiny code, suggesting functions that don't exist, using incorrect syntax, or producing code that simply doesn't work.

If you’re improving your Shiny setup, there’s another tool to consider. Positron supports both R and Python in a polished, familiar IDE.

This isn't surprising. LLMs like GPT and Claude have had limited exposure to Shiny code during their training, leaving them with significant knowledge gaps about this specialized framework.

Introducing the @shiny Tag in VS Code

Posit (formerly RStudio) has recently addressed this challenge with their Shiny VS Code extension, featuring a specialized integration with GitHub Copilot. The key innovation is simple but powerful: adding @shiny to your Copilot prompts.

When you use this tag, the extension performs "prompt stuffing", essentially injecting comprehensive RShiny and Shiny for Python documentation and context into the conversation with the LLM. This gives Copilot the knowledge it needs to generate reliable, accurate Shiny code.

How It Works

Using the feature is straightforward:

1. Install the Posit Shiny VS Code extension
2. Open the Copilot chat in VS Code
3. Begin your prompt with @shiny
4. Ask for the Shiny code you need

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Real Benefits, Not Hype

The value of this integration isn't about typing less code, it's about reliability. Here's what it means for different stakeholders:

For Developers:

• Function recommendations that actually exist in the Shiny ecosystem
• Proper syntax suggestions that follow Shiny conventions
• Less time spent debugging hallucinated code

For Team Managers:

• More consistent code quality across the team
• Reduced technical debt from improper implementations
• Faster onboarding for team members less familiar with Shiny

Before vs. After

It’s best to look at a concrete example.

Without @shiny the responses are completely unpredictable when it comes to the RShiny world. The first response caught me by surprise, generated with Claude Sonnet 3.7.

Why This Matters

This integration brings RShiny development closer to the experience developers have with mainstream languages when using Copilot. It shows how specialized frameworks can overcome the limitations of general-purpose LLMs through thoughtful integrations.

For Appsilon clients and the broader RShiny community, this means being able to leverage modern coding tools while maintaining the quality and reliability that production applications demand.

Getting Started

To try this feature:

1. Install the Shiny VS Code extension
2. Make sure GitHub Copilot is enabled in your VS Code
3. Open a Shiny project and start using the @shiny tag in your Copilot prompts

Conclusion

AI coding tools aren’t perfect, but they’re getting closer. With the @shiny tag and Posit's VS Code extension, you can get Copilot to generate cleaner, more reliable code that actually understands Shiny. It’s a small change that makes a big difference especially when you're building production-ready applications.

Reliable code starts with the right tools and the right habits. Grab our Level Up Your R/Shiny Team Skills ebook to help your team build both.