Creating Apps For LLMs
SkillProductivityGuides your agent step-by-step through building, testing, and publishing apps that run inside ChatGPT.
Available today. Use it from your connected AI after setup.
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Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Creating Apps For LLMs skill
About this skill
Guide developers through creating and updating ChatGPT apps. Covers the full lifecycle: brainstorming ideas against UX guidelines, bootstrapping projects, implementing tools/views, debugging, running dev servers, deploying and connecting apps to ChatGPT. Use when a user wants to create or update a C
What this skill tells your AI
The instructions your AI receives, as published by alpic-ai/skybridge in skills/chatgpt-app-builder/SKILL.md and read by ahel’s review.
ChatGPT apps are conversational experiences that extend ChatGPT 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 ChatGPT 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.
Building an ecommerce app? → Read ecommerce.md first.
No SPEC.md? → Read discover.md first. Nothing else until SPEC.md exists.
SPEC.md exists? → Read SPEC.md, then follow architecture.md to design the change. Update SPEC.md, then read the relevant Implementation references below before writing code.
Migrating from Skybridge < 0.36.x? → Read migrate-to-v1.md first. Users may reference skybridge >= 0.36.x as v1.
Migrating from Skybridge 1.x to 2.x? → Fetch the v2.0.0 release notes first and follow them.
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 connection
- Evals → evals.md: when checking that a real model reaches the right tools from natural prompts, in a test
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 view data fetching
- State and context → state-and-context.md: when persisting view UI state and updating LLM context
- Prompt LLM → prompt-llm.md: when view 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
- Assets and styling → assets-and-styling.md: when adding images, fonts or CSS to views
- 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 Directory → publish.md: when ready to submit for review
Full API docs: https://docs.skybridge.tech/api-reference.md
Release notes & changelog: https://skybridge.tech/changelog.md
Signals
- GitHub stars
- 2k
- Forks
- 141
- Last commit
- Sep 2026
ahel review
K7info
secret-appetite (in references/publish.md)
Automated review, not a security audit. Ruleset v1+k2.
Advanced
- Item type
- skill
- Key
skybridge-chatgpt-app-builder- Source
- github.com/alpic-ai/skybridge