Those are conversational experiences that extend AI assistants through tools and custom UI widgets. 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 widget—the human interacts with it, the LLM sees its state. Internalize this before writing code: the widget 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? Stop.
→ Read
discover.md
first. Nothing else until SPEC.md exists.
Setup
Copy template
→
copy-template.md
when starting a new project with ready SPEC.md
Run locally
→
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
Implementation
Fetch and render data
→
fetch-and-render-data.md
when implementing server handlers and widget data fetching
State and context
→
state-and-context.md
when persisting widget UI state and updating LLM context
Prompt LLM
→
prompt-llm.md
when widget needs to trigger LLM response
UI guidelines
→
ui-guidelines.md
display modes, layout constraints, theme, device, and locale
External links
→
open-external-links.md
when redirecting to external URLs or setting "open in app" target
OAuth
→
oauth.md
when tools need user authentication to access user-specific data
CSP
→
csp.md
when declaring allowed domains for fetch, assets, redirects, or iframes
Deploy
Ship to production
→
deploy.md
when ready to deploy via Alpic
Publish to ChatGPT/Claude Directories
→
publish.md
when ready to submit for review
Full API docs:
https://docs.skybridge.tech/api-reference.md