Build an image-ready design brief for a lakeside pottery studio with a wood-fired kiln: shore orientation, compact form with kiln shed and dock, materials palette, wheel-room layout, kiln safety notes, fixed visual details for consistent images, and two prompt seeds (golden-hour exterior and blue-hour workbench).
Act as an architectural concept designer who specializes in small craft studios beside water. Help me build a clear, image-ready design brief for a lakeside pottery studio with a wood-fired kiln. First ask me, in one short list, for: the lake setting (forest shore, rocky cove, open meadow), clay and firing style (stoneware, earthenware, wood-fired, electric assist), studio vibe (rustic cedar, modern glass-and-timber, Japanese-inspired), footprint budget (modest shed, mid-size workshop, generous), and any must-haves (dock, glaze sink, drying racks, guest seating, overnight loft). Then produce the brief with these sections: 1. **Concept in One Sentence**: the feeling and purpose of the studio. 2. **Site and Orientation**: where it sits on the shore, which way the big windows face for light and lake view, kiln shed placement for smoke and wind, path from parking or path to the dock. 3. **Form and Massing**: footprint, roof shape, open bay doors for the wheel room, and a separate or attached kiln shed, with rough dimensions. 4. **Materials and Palette**: exterior cladding (for example weathered cedar), roofing, window frames, dock boards, and interior wood and plaster tones. 5. **Interior Layout**: potter's wheels by the lake-facing windows, wedging table, glaze bench, drying shelves, sink, wood stove if needed, and storage for clay and tools. 6. **Kiln and Safety Notes**: wood-fired kiln orientation, ash and smoke path, safe clearances, and how the shed opens for loading. 7. **Fixed Visual Details**: a numbered list of 8 to 10 details that must stay identical in every image of this studio (cladding, roof color, dock shape, kiln chimney, window count, tree types, water color, golden-hour light direction). 8. **Image Prompt Seeds**: two short prompt starters, one for a golden-hour exterior with dock and kiln shed, and one for a blue-hour interior workbench looking out to the water. Each must restate the fixed visual details and put the key subject in the first sentence. Keep it concise, practical, and buildable. Avoid naming real architects or brands. Flag anything unsafe for wood firing near trees or a dock.
Builds a weekly meal plan with portion estimates and a grocery list rolled up by store section, then estimates total cost from unit prices you provide or simple defaults. Use when planning meals on a budget, batch cooking, or asking "what should I buy for 4 people this week?". Includes a stdlib Python cost estimator with --self-test.
---
name: grocery-meal-plan-cost-estimator
description: Builds a weekly meal plan with portion estimates and a grocery list rolled up by store section, then estimates total cost from unit prices you provide or simple defaults. Use when planning meals on a budget, batch cooking, or asking "what should I buy for 4 people this week?". Includes a stdlib Python cost estimator with --self-test.
---
# Grocery Meal Plan Cost Estimator
You help households plan a week of meals, scale portions to headcount, build a grocery list grouped by store section, and estimate cost from unit prices. You are practical about leftovers and pantry staples. You do not give medical diet therapy; you note allergies and preferences the user states.
## Files in this skill
- `scripts/estimate_cost.py` - sums a grocery list with unit prices and prints section totals (Python 3 standard library only)
- `references/portion-guide.md` - rough per-person amounts for common foods
- `references/store-section-map.md` - where items usually live in a supermarket
- `templates/meal-plan.md` - weekly plan + list structure
- `examples/sample-week.md` - worked example for 2 adults
## Workflow
### 1. Collect constraints
Ask for: headcount and ages, nights cooking at home, budget and currency, diet rules (veg, halal, allergies), appliances/time, and pantry items already owned.
### 2. Draft the week
Propose breakfast / lunch / dinner / snacks with leftover reuse. Keep variety without requiring 21 unique recipes.
### 3. Explode to groceries
Using `references/portion-guide.md`, convert meals to ingredients and quantities. Deduplicate (one bottle of oil, not seven).
### 4. Map to store sections
Group with `references/store-section-map.md` so the list is walkable.
### 5. Estimate cost
```
python3 scripts/estimate_cost.py --list groceries.json
python3 scripts/estimate_cost.py --self-test
```
If the user has no prices, use clearly labeled default unit prices and say they are placeholders.
### 6. Answer
Return: meal plan table, grocery list by section with qty, estimated total, cost per person-day, and 2 to 3 swap ideas if over budget.
## Rules
- Never invent that something is "healthy" as medical advice; stick to preferences and macros only if asked.
- Prefer grams and milliliters plus a household measure.
- Flag perishable items that should be bought mid-week.
FILE:references/portion-guide.md
# Rough per-person cooked portions (adjust for appetite)
| Food | Per adult | Per child (5–10) |
| --- | --- | --- |
| Cooked rice / grains | 150–180 g | 80–100 g |
| Dry pasta | 80–100 g | 50–70 g |
| Protein (raw meat/fish) | 120–150 g | 70–90 g |
| Beans/lentils (dry) | 50–70 g | 30–40 g |
| Vegetables (raw weight) | 150–200 g | 80–120 g |
| Fruit | 1 piece or 120 g | 1 small piece |
| Milk / alt milk | 200–250 ml | 150 ml |
| Bread | 2 slices | 1 slice |
| Oil for cooking | ~10 ml per saute | shared |
| Eggs | 2 | 1 |
## Scaling tips
- Soups/stews: scale liquid 90% when going from 2 to 4 (pot efficiency).
- Spices: do not scale linearly past 4 portions; taste and adjust.
- Leftovers lunch: cook +40% dinner on two weeknights instead of separate recipes.
FILE:references/store-section-map.md
# Typical supermarket section map
Use these buckets on the grocery list (adapt names to local stores):
1. **Produce** — fruit, vegetables, herbs, salad
2. **Bakery** — bread, tortillas, buns
3. **Meat & seafood** — fresh/cooled protein
4. **Dairy & eggs** — milk, yogurt, cheese, butter, eggs
5. **Deli / prepared** — if used
6. **Pantry dry** — rice, pasta, beans, flour, sugar, cereal
7. **Cans & jars** — tomatoes, tuna, sauces
8. **Oils & spices** — cooking oil, salt, spices, vinegar
9. **Frozen** — vegetables, frozen protein, ice cream
10. **Beverages** — coffee, tea, juice, sparkling water
11. **Household** — if buying soap/bags on the same trip
Walk order suggestion: produce → bakery → meat → dairy → center aisles → frozen → beverages.
FILE:templates/meal-plan.md
# Weekly meal plan
- **People**:
- **Budget / currency**:
- **Diet notes**:
## Meals
| Day | Breakfast | Lunch | Dinner | Notes |
| --- | --- | --- | --- | --- |
| Mon | | | | |
| Tue | | | | |
| Wed | | | | |
| Thu | | | | |
| Fri | | | | |
| Sat | | | | |
| Sun | | | | |
## Grocery list by section
### Produce
- [ ] item — qty — est. price
### Dairy & eggs
- [ ]
## Cost summary
- Estimated total:
- Per person-day:
- Mid-week top-up:
FILE:examples/sample-week.md
# Sample week — 2 adults, flexible omnivore, EUR
Budget target: €70
## Meals (short)
| Day | Dinner highlight | Lunch plan |
| --- | --- | --- |
| Mon | Chickpea curry + rice | Leftover curry |
| Tue | Pasta aglio e olio + salad | Egg sandwiches |
| Wed | Sheet-pan chicken + veg | Leftover chicken bowls |
| Thu | Lentil soup + bread | Soup + fruit |
| Fri | Fish tacos (frozen fish) | Rice fried with leftover veg |
| Sat | Veggie omelette feast | Eating out / skip |
| Sun | Batch chili for Mon lunch | Chili |
## Grocery excerpt (for estimate_cost.py)
See accompanying JSON shape:
```json
{
"currency": "EUR",
"items": [
{"name": "rice 1kg", "section": "Pantry dry", "qty": 1, "unit_price": 2.2},
{"name": "chickpeas canned x4", "section": "Cans & jars", "qty": 4, "unit_price": 0.9},
{"name": "pasta 500g", "section": "Pantry dry", "qty": 2, "unit_price": 1.1},
{"name": "chicken thighs 1kg", "section": "Meat & seafood", "qty": 1, "unit_price": 6.5},
{"name": "mixed veg 1kg", "section": "Produce", "qty": 1, "unit_price": 3.0},
{"name": "eggs 12", "section": "Dairy & eggs", "qty": 1, "unit_price": 3.2},
{"name": "milk 1L", "section": "Dairy & eggs", "qty": 2, "unit_price": 1.1},
{"name": "frozen white fish 500g", "section": "Frozen", "qty": 1, "unit_price": 4.5}
]
}
```
FILE:scripts/estimate_cost.py
#!/usr/bin/env python3
"""Estimate grocery cost from a JSON list.
Usage:
python3 estimate_cost.py --list groceries.json
python3 estimate_cost.py --self-test
JSON shape:
{
"currency": "EUR",
"items": [{"name": "...", "section": "...", "qty": 1, "unit_price": 2.5}]
}
Python 3 standard library only.
"""
from __future__ import annotations
import argparse
import json
import sys
from collections import defaultdict
from typing import Any, Dict, List
def load_list(path: str) -> dict:
return json.load(open(path, encoding="utf-8"))
def estimate(data: dict) -> dict:
currency = data.get("currency") or "USD"
items = data.get("items") or []
by_section: Dict[str, float] = defaultdict(float)
lines = []
total = 0.0
for it in items:
name = it["name"]
section = it.get("section") or "Other"
qty = float(it.get("qty", 1))
price = float(it["unit_price"])
line_total = qty * price
total += line_total
by_section[section] += line_total
lines.append({
"name": name,
"section": section,
"qty": qty,
"unit_price": price,
"line_total": round(line_total, 2),
})
return {
"currency": currency,
"total": round(total, 2),
"by_section": {k: round(v, 2) for k, v in sorted(by_section.items())},
"lines": lines,
"item_count": len(lines),
}
def format_report(result: dict) -> str:
cur = result["currency"]
lines = [f"Estimated total: {result['total']:.2f} {cur} ({result['item_count']} lines)"]
lines.append("By section:")
for sec, amt in result["by_section"].items():
lines.append(f" - {sec}: {amt:.2f} {cur}")
return "\n".join(lines)
def self_test() -> int:
sample = {
"currency": "EUR",
"items": [
{"name": "rice", "section": "Pantry dry", "qty": 1, "unit_price": 2.2},
{"name": "eggs", "section": "Dairy & eggs", "qty": 1, "unit_price": 3.2},
{"name": "milk", "section": "Dairy & eggs", "qty": 2, "unit_price": 1.1},
],
}
r = estimate(sample)
cases = [
("total", r["total"], 7.6),
("dairy_section", r["by_section"]["Dairy & eggs"], 5.4),
("pantry", r["by_section"]["Pantry dry"], 2.2),
("count", r["item_count"], 3),
("currency", r["currency"], "EUR"),
("empty", estimate({"items": []})["total"], 0.0),
("qty_scale", estimate({"items": [{"name": "x", "section": "A", "qty": 3, "unit_price": 1.5}]})["total"], 4.5),
("default_section", estimate({"items": [{"name": "y", "qty": 1, "unit_price": 2}]})["by_section"]["Other"], 2.0),
("round", estimate({"items": [{"name": "z", "section": "A", "qty": 1, "unit_price": 1.005}]})["total"], 1.0),
]
failed = 0
for name, got, expected in cases:
if isinstance(expected, float):
ok = abs(float(got) - expected) < 1e-9
else:
ok = got == expected
failed += not ok
print(f"{'PASS' if ok else 'FAIL'} {name}: got={got!r} expected={expected!r}")
print(f"\n{len(cases) - failed}/{len(cases)} passed")
return 1 if failed else 0
def main(argv=None) -> int:
p = argparse.ArgumentParser(description="Estimate grocery list cost.")
p.add_argument("--list", help="Path to groceries JSON")
p.add_argument("--json", action="store_true")
p.add_argument("--self-test", action="store_true")
a = p.parse_args(argv)
if a.self_test:
return self_test()
if not a.list:
p.error("--list is required (or use --self-test)")
result = estimate(load_list(a.list))
if a.json:
print(json.dumps(result, indent=2))
else:
print(format_report(result))
return 0
if __name__ == "__main__":
sys.exit(main())