(Generated by [[Claude|Claude]] using the Exa and Sequential-Thinking tools)
This comprehensive guide will help you create a visually engaging, ADHD-optimized Obsidian vault using Emoji Kitchen combinations. You'll learn how to transform your notes, journal entries, and mood tracking into a vibrant, attention-grabbing system that works with your brain instead of against it.
ADHD brains often:
(Generated by [[Claude|Claude]] 3.7 Sonnet using the Exa and Sequential-Thinking tools)
This guide builds on our previous recommendations for using Emoji Kitchen combinations in Obsidian, but adds powerful automation to make the system more sustainable. Since maintaining complex systems can be challenging for ADHD brains, automation is key to reducing friction and keeping your system working for you.
After researching how the websites like emojikitchen.dev work, I've discovered that all Emoji Kitchen combinations are stored as PNG images on Google's servers. They follow a predictable URL pattern:
| 2025-11-05T02:06:56.9589375Z Current runner version: '2.329.0' | |
| 2025-11-05T02:06:56.9613228Z ##[group]Runner Image Provisioner | |
| 2025-11-05T02:06:56.9614222Z Hosted Compute Agent | |
| 2025-11-05T02:06:56.9614814Z Version: 20251016.436 | |
| 2025-11-05T02:06:56.9615543Z Commit: 8ab8ac8bfd662a3739dab9fe09456aba92132568 | |
| 2025-11-05T02:06:56.9616559Z Build Date: 2025-10-15T20:44:12Z | |
| 2025-11-05T02:06:56.9617227Z ##[endgroup] | |
| 2025-11-05T02:06:56.9617889Z ##[group]Operating System | |
| 2025-11-05T02:06:56.9618506Z Ubuntu | |
| 2025-11-05T02:06:56.9619007Z 24.04.3 |
This guide covers migrating your Reminders app from local models (whisper.cpp + Llama) to Cloudflare Workers AI, eliminating the need for users to download 1+ GB of model files.
| name | description | tools | model | color |
|---|---|---|---|---|
house-research |
Research specialist for large codebase searches. Use proactively when searching 20+ files or needing to find patterns across the codebase. Returns condensed findings with source references. |
Read, Grep, Glob, Task |
inherit |
pink |
You are the House Research Agent, a specialized AI assistant focused on efficient code and document searching.
name: web-research-specialist description: Use this agent when you need to search the web for information, retrieve content from URLs, or gather external context that would otherwise consume significant tokens in the main conversation. This agent is specifically designed to offload web-based research tasks and return concise, relevant summaries.\n\nExamples:\n\n\nContext: User needs current information about a technology or API that may have changed recently.\nuser: "What are the latest features in Python 3.13?"\nassistant: "I'll use the web-research-specialist agent to search for the latest Python 3.13 features and provide you with an up-to-date summary."\nThe user needs current information that requires web search. Launch the web-research-specialist agent to gather this information efficiently.\n\n\n\nContext: User is asking about documentation or implementation details for an external library.\nuser: "How do I implement OAuth2 with the requests libra
name: quick-code-patch description: Use this agent when you need to implement small, focused code changes of 0-250 lines. This includes: fixing imports, applying git diff suggestions, adding small features, implementing proposed changes, fixing bugs, refactoring small sections, updating dependencies, or making configuration adjustments. This agent is optimized for speed and should be your first choice for quick, surgical code modifications.\n\nExamples:\n- User: "Can you add error handling to the login function?"\n Assistant: "I'll use the quick-code-patch agent to add error handling to the login function."\n \n\n- User: "The import statement in utils.py is broken, can you fix it?"\n Assistant: "Let me use the quick-code-patch agent to fix that import."\n \n\n- User: "I need to add a new endpoint to the API for fetching user preferences"\n Assistant: "I'll use the quick-code-patch agent to add that endpo
(yes this is from an AI. This is from Claude 3
Table of Contents:
| import os | |
| import json | |
| from subprocess import run | |
| try: | |
| import wget | |
| except ImportError: | |
| run(["pip", "install", "wget", "--upgrade"]) | |
