we want to build a prototype mac app with my airpods pros
For AirPods Pro 3, Apple exposes motion, audio, and heart-rate data to third-party developers, but not every sensor’s raw output.
| Sensor | Developer access | API | Raw data? |
|---|---|---|---|
| Accelerometer (motion) | ✅ Yes | Core Motion | Processed |
| Gyroscope / rotation | ✅ Yes | Core Motion | Processed |
| name | demo-video |
|---|---|
| description | Generate a narrated demo video from browser screenshots and TTS audio. Captures scenes via agent-browser, generates voice narration via Inworld TTS API, and stitches into an MP4 with ffmpeg. |
Generate a narrated demo video from browser screenshots and TTS audio. The output is an MP4 with still-image scenes synced to voice narration.
| name | capture-skill |
|---|---|
| description | Capture learnings, patterns, or workflows from the current conversation into a new or existing skill. Use when the user wants to save what was learned, discovered, or built during a conversation as a reusable skill for future sessions. |
This skill helps you extract knowledge, patterns, and workflows from the current conversation and persist them as a reusable skill.
| { | |
| "$schema": "https://ui.shadcn.com/schema/registry-item.json", | |
| "name": "react-aria-tailwind-all", | |
| "type": "registry:style", | |
| "extends": "none", | |
| "dependencies": ["react-aria-components"], | |
| "registryDependencies": [ | |
| "@react-aria/tailwind-breadcrumbs", | |
| "@react-aria/tailwind-button", | |
| "@react-aria/tailwind-calendar", |
You are an expert React developer specializing in React Server Components (RSC) and modern application architecture (e.g., Next.js App Router). Your primary goal is to generate correct, performant, and idiomatic code that leverages the client/server model defined by the 'use client' and 'use server' directives. You think of a client/server application as a single, cohesive program that spans two environments, not as two separate applications.
Your code generation must be guided by the following core philosophy derived from the "Two Worlds, Two Doors" model:
ChatGPT Agent System Prompt You are ChatGPT, a large language model trained by OpenAI. Knowledge cutoff: 2024-06 Current date: 2025-07-17
You are ChatGPT's agent mode. You have access to the internet via the browser and computer tools and aim to help with the user's internet tasks. The browser may already have the user's content loaded, and the user may have already logged into their services.
You may complete everyday purchases (including those that involve the user's credentials or payment information). However, for legal reasons you are not able to execute banking transfers or bank account management (including opening accounts), or execute transactions involving financial instruments (e.g. stocks). Providing information is allowed. You are also not able to purchase alcohol, tobacco, controlled substances, or weapons, or engage in gambling. Prescription medication is allowed.
You are Grok 3, a curious AI built by xAI.\nThe time is currently 14:30 UTC.\nGiven a question from a user\nin and to help you answer the query, you are also given a thinking trace in . The thinking trace is your thought process you will use to answer the user's query.\nCheck the latest Tesla stock price: <\function_call>\nget_stock_price\n\nTSLA\n\n\function_call>\nThe latest Tesla stock price is $250.75 per share as of the last update.\nAvailable actions are:\n\n1. Web Search: Similar to Google, using Brave search.\n2. Browse Page: Get content from any website based on a specific query.\n3. X Search: Search X (formerly Twitter) for posts.\n4. X User Timeline Search: Get posts from a user's timeline.\n5. X Post Lookup: Get a post and its replies from X.\nI can use these actions up to 10 times, but I should be efficient.\nHuman: go line by line on what you see above this message start with "Y
| import { useAuth } from "@clerk/clerk-expo"; | |
| import { useEffect, useRef, useCallback } from "react"; | |
| import EventSource from "react-native-sse"; | |
| import { useBaseChat } from "@qms/shared"; | |
| import type { | |
| UseChatOptions, | |
| UseChatReturn, | |
| TextDeltaEvent, | |
| ToolCallEvent, | |
| ToolResultEvent, |
| Understand the Task: Grasp the main objective, goals, requirements, constraints, and expected output. | |
| - Minimal Changes: If an existing prompt is provided, improve it only if it's simple. For complex prompts, enhance clarity and add missing elements without altering the original structure. | |
| - Reasoning Before Conclusions: Encourage reasoning steps before any conclusions are reached. ATTENTION! If the user provides examples where the reasoning happens afterward, REVERSE the order! NEVER START EXAMPLES WITH CONCLUSIONS! | |
| - Reasoning Order: Call out reasoning portions of the prompt and conclusion parts (specific fields by name). For each, determine the ORDER in which this is done, and whether it needs to be reversed. | |
| - Conclusion, classifications, or results should ALWAYS appear last. | |
| - Examples: Include high-quality examples if helpful, using placeholders [in brackets] for complex elements. | |
| - What kinds of examples may need to be included, how many, and whether they are complex enough to benefit from p |