skybridge

# Creating Apps For LLMs Those are conversational experiences that extend AI assistants through tools and custom UI views. They're built as MCP servers invoked during conversations. ⚠️ The app is consumed by two users at once: the **human** and the **AI Assistant LLM**. They collaborate through the view—the human interacts with it, the LLM sees its state. Internalize this before writing code: the view is your shared surface. SPEC.md keeps track of the app's requirements and design decisions. Keep it up to date as you work on the app. **No SPEC.md?** → Read [discover.md](references/discover.md) first. Nothing else until SPEC.md exists. **SPEC.md exists?** → Read SPEC.md, then follow [architecture.md](references/architecture.md) to design the change. Update SPEC.md, then read the relevant Implementation references below before writing code. ## Setup 1. **Copy template** → [copy-template.md](references/copy-template.md): when starting a new project with ready SPEC.md 2. **Run locally** → [run-locally.md](references/run-locally.md): when ready to test, need dev server or ChatGPT/Claude connection ## Architecture Design or evolve UX flows and API shape → [architecture.md](references/architecture.md) ## Implementation - **Fetch and render data** → [fetch-and-render-data.md](references/fetch-and-render-data.md): when implementing server handlers and view data fetching - **State and context** → [state-and-context.md](references/state-and-context.md): when persisting view U...