🎁 Get the FREE AI Skills Starter Guide β€” Subscribe β†’
BytesAgainBytesAgain
BytesAgain β€Ί Skills β€Ί Restaurants
πŸ¦€ ClawHub

Restaurants

by @ivangdavila

Build a personal restaurant system for tracking places to try, favorites, and dining memories.

Versionv1.0.0
Downloads1,442
Installs1
Stars⭐ 2
#clawhub
TERMINAL
clawhub install restaurants

πŸ“– About This Skill

name: Restaurants description: Build a personal restaurant system for tracking places to try, favorites, and dining memories. metadata: {"clawdbot":{"emoji":"🍽️","os":["linux","darwin","win32"]}}

Core Behavior

  • User mentions restaurant β†’ offer to save with notes
  • User asks for recommendation β†’ check their saved places first
  • User returns from meal β†’ help document experience
  • Create ~/restaurants/ as workspace

    • File Structure

    ~/restaurants/
β”œβ”€β”€ to-try/
β”œβ”€β”€ favorites/
β”œβ”€β”€ visited/
β”‚   └── 2024/
β”œβ”€β”€ by-cuisine/
└── by-occasion/

    To-Try Entry

    # sushi-nakazawa.md

    Location
    
West Village, NYC
    Cuisine
    
Omakase sushi
    Source
    
Friend recommendation
    Price Range
    
$$$$
    Notes
    
Need reservation weeks ahead

    Visited Entry

    # la-mercerie-2024-03.md

    Date
    
March 15, 2024
    Occasion
    
Anniversary dinner
    What We Ordered
    

  • Burrata (excellent)
    • 

  • Duck breast (slightly dry)
    • 

  • Chocolate soufflΓ© (must order)
    • Verdict
    
β˜…β˜…β˜…β˜…β˜† β€” Would return for brunch

    Favorites

    # joes-pizza.md

    Go-To Order
    
Plain slice, extra crispy
    Best For
    
Quick lunch, late night
    Notes
    
Cash only, expect line

    By-Cuisine and By-Occasion

    Simple lists linking to favorites: 
    # date-night.md

  • La Mercerie β€” beautiful space
    • 

  • Via Carota β€” classic Village
    • 

  • Carbone β€” never fails
    •

    What To Track

  • Location and neighborhood
  • Cuisine type
  • Price range: $ to $$$$
  • Reservation: needed? how far ahead?
  • Standout dishes
  • Rating after visit

    • Surfacing Recommendations

    When user asks "where should we eat":
  • Ask occasion and cuisine preference
  • Check THEIR saved places first
  • Suggest from their data before general knowledge

    • What To Surface

  • "You haven't tried that sushi place on your list"
  • "Last Italian you loved was L'Artusi"
  • "For date night you rated La Mercerie highest"

    • Progressive Enhancement

  • Start: add 5 places to try
  • After meals: quick entry with verdict
  • Build cuisine and occasion lists over time

    • What NOT To Do

  • Recommend unsaved places without asking
  • Forget dietary restrictions
  • Over-organize β€” simple notes work

    • πŸ“‹ Tips & Best Practices

    Need reservation weeks ahead ```