WineBuddy Skill

Query and explore your personal wine cellar database.

Step 1: Ensure winebuddy is installed and up-to-date

if [ ! -d ~/.winebuddy ]; then
  git clone https://github.com/jasondchambers/winebuddy.git ~/.winebuddy
fi && cd ~/.winebuddy && git pull

Step 2: Run Commands

cd ~/.winebuddy && uv run python winebuddy.py <command>

Commands Overview

Command	Purpose
query	Search and filter wines
discover <type>	List distinct values (colors, varietals, regions, etc.)

---

Query Command

Search wines with filters:

cd ~/.winebuddy && uv run python winebuddy.py query [OPTIONS]

Filter Options

Option	Description	Example
--color	Wine color	--color Red
--varietal	Grape variety (partial match)	--varietal "Pinot Noir"
--producer	Producer name (partial match)	--producer "Patricia Green"
--country	Country of origin	--country Italy
--region	Region (partial match)	--region Willamette
--vintage	Exact vintage year	--vintage 2019
--vintage-min	Minimum vintage	--vintage-min 2015
--vintage-max	Maximum vintage	--vintage-max 2018
--score-min	Minimum score (professional or community)	--score-min 90
--in-stock	Only wines with quantity > 0	--in-stock
--ready	Wines in their drinking window	--ready

Output Options

Option	Description
--format table	ASCII table (default)
--format json	JSON output
--format csv	CSV output
--sort vintage|producer|score|price|wine_name	Sort field
--desc	Sort descending
--limit N	Limit results

JSON Output Fields

{
  "id": 1,
  "wine_name": "Wine name",
  "vintage": 2019,
  "producer": "Winery",
  "varietal": "Pinot Noir",
  "color": "Red",
  "country": "USA",
  "region": "Oregon",
  "subregion": "Willamette Valley",
  "quantity": 3,
  "value": 75.95,
  "professional_score": 93.5,
  "community_score": 91.2,
  "begin_consume": 2024,
  "end_consume": 2032
}

---

Discover Command

List distinct values in the cellar:

cd ~/.winebuddy && uv run python winebuddy.py discover colors
cd ~/.winebuddy && uv run python winebuddy.py discover varietals
cd ~/.winebuddy && uv run python winebuddy.py discover producers
cd ~/.winebuddy && uv run python winebuddy.py discover countries
cd ~/.winebuddy && uv run python winebuddy.py discover regions
cd ~/.winebuddy && uv run python winebuddy.py discover vintages

---

Example Queries

Inventory Questions

# All wines in stock
cd ~/.winebuddy && uv run python winebuddy.py query --in-stock --format table

# Most valuable bottles
cd ~/.winebuddy && uv run python winebuddy.py query --in-stock --sort price --desc --limit 5 --format json

# Oldest vintages
cd ~/.winebuddy && uv run python winebuddy.py query --in-stock --sort vintage --limit 5 --format json

Finding Specific Wines

# Italian wines
cd ~/.winebuddy && uv run python winebuddy.py query --in-stock --country Italy --format json

# Wines from a region
cd ~/.winebuddy && uv run python winebuddy.py query --in-stock --region "Willamette" --format json

# Specific producer
cd ~/.winebuddy && uv run python winebuddy.py query --in-stock --producer "Patricia Green" --format json

# Specific varietal
cd ~/.winebuddy && uv run python winebuddy.py query --in-stock --varietal "Nebbiolo" --format json

Drinking Window Questions

# Ready to drink now
cd ~/.winebuddy && uv run python winebuddy.py query --in-stock --ready --format json

# Top rated wines
cd ~/.winebuddy && uv run python winebuddy.py query --in-stock --sort score --desc --limit 10 --format json

# Wines from specific vintage range
cd ~/.winebuddy && uv run python winebuddy.py query --in-stock --vintage-min 2015 --vintage-max 2018 --format json

---

Wine Pairing

For food pairing recommendations, use these guidelines:

Dish Type	Recommended Varietals
Red meat (beef, lamb)	Cabernet Sauvignon, Merlot, Syrah, Red Bordeaux Blend
Poultry (chicken, turkey)	Pinot Noir, Chardonnay
Pork	Grenache, Tempranillo, Riesling
Fish (light)	Sauvignon Blanc, Pinot Grigio, Arneis
Salmon/rich fish	Pinot Noir, Chardonnay, Champagne Blend
Seafood/shellfish	Champagne Blend, Sparkling, Sauvignon Blanc
Pasta (red sauce)	Sangiovese, Nebbiolo
Pasta (cream sauce)	Chardonnay
Spicy food	Riesling, Gewürztraminer, Frappato

Pairing Query Strategy

1. Identify appropriate varietals from the table above
2. Query wines by varietal, sorted by score:

   cd ~/.winebuddy && uv run python winebuddy.py query --in-stock --varietal "Pinot Noir" --format json --sort score --desc --limit 5

3. Check drinking windows in results to identify:
   • Drink Soon: end_consume < 2026 (current year)
   • Best Available: Highest scores regardless of window

Pairing Response Format

## Wine Pairing Recommendations for [Dish]

### Drink Soon (Past Drinking Window)
1. **[Wine]** ([Vintage]) - Score: [X] | Value: $[X] | Window: [X-X]
   Why it pairs: [rationale]

### Best Available (Special Occasions)
1. **[Wine]** ([Vintage]) - Score: [X] | Value: $[X] | Window: [X-X]
   Why it pairs: [rationale]