Skill: adamsellers/recipe-chef (version 1.0.0)

--- name: recipe-chef description: Discover, compare, and tailor recipes from available ingredients, kitchen gear, dietary goals, and taste preferences. Use when a user wants meal ideas from pantry items, a bench or fridge photo, a "surprise me" cooking suggestion, a recurring meal plan for the family or for training goals, recipe options sourced from the web, or help learning and applying food preferences such as healthy, indulgent, vegan, kid-friendly, high-protein, low-effort, or appliance-specific cooking. --- # Recipe Chef Use this skill to turn ingredients, kitchen context, and taste signals into practical meal options. ## Workflow 1. Determine the input mode. - Treat typed ingredient lists, pantry notes, and "I have..." prompts as ingredient mode. - Treat food, fridge, or bench photos as image mode. Use image analysis first to identify likely ingredients and visible kitchen gear. - Treat broad prompts like "surprise me", "what should I cook", or "give me dinner ideas" as surprise mode. - Treat requests like "meal plan for the week", "family meal plan", "training meal plan", or "plan my dinners" as meal-plan mode. 2. Build a cooking brief. Capture or infer: - available ingredients - likely pantry staples - dietary preferences or restrictions - desired style, healthy vs indulgent, comfort food vs light, kid-friendly vs adventurous - available time and effort tolerance - serving count and audience, especially children - appliances and cookware, such as air fryer, wok, Dutch oven, soup pot, sheet pans, food processor - methods to avoid, for example deep frying or lots of cleanup - urgency signals, such as produce that should be used soon or leftovers likely needing priority 3. Fill only the critical gaps. Ask at most 2 to 4 compact questions when missing information would materially change the recommendation. Prefer moving forward with stated assumptions over conducting a long intake. 4. Discover candidates. Search the web for a small set of strong recipes. Prefer reputable recipe publishers with clear ingredients, timing, and method notes. Fetch the most promising pages and compare them. 5. Rank and tailor. Score options by: - ingredient fit - equipment fit - time fit - preference fit - dietary fit - family fit, especially for kid-friendly cooking - likely taste payoff - use-soon value for ingredients that appear perishable or urgent 6. Present concise options. Usually give 3 options. For each option include: - dish name - why it fits - approximate time - key missing ingredients, if any - whether it suits the user's kitchen gear 7. In image mode, prefer a mini meal plan over disconnected recipe ideas. Structure it as: - best tonight - second best - use-it-up follow-up meal, lunch, or snack - one option that becomes great with 1 or 2 extra ingredients, if relevant 8. Ask one smart follow-up at most when it will meaningfully improve the plan. Prefer questions like: - do you have a protein not shown, such as chicken, mince, beans, or tofu? - quick and kid-safe, or tastier and messier? - pan, oven, or air fryer? 9. On selection, convert the winning option into a practical plan. Provide: - a cleaned-up ingredient list - substitutions based on what the user has - step-by-step method - kid tweaks or heat adjustments when relevant - air fryer, oven, or stovetop adaptation when useful ## Preference harvesting Actively notice preference signals during the conversation. Useful categories: - favorite cuisines and flavors - disliked ingredients or textures - healthy, indulgent, vegan, vegetarian, high-protein, low-carb, budget-conscious, quick weeknight - spice tolerance - kid-friendly needs - preferred proteins and vegetables - pantry staples commonly kept on hand - kitchen confidence level - preferred appliances and cookware - cleanup tolerance, one-pan preference, batch cooking interest Treat recurring food and kitchen preferences as durable memory candidates, not one-off chat trivia. ## Automatic preference memory When the session supports memory and the user expresses a stable preference, capture it proactively. Good memory candidates: - recurring nutrition goals, high protein, fat loss, balanced family eating - durable dislikes or avoidances - favorite cuisines or reliable family wins - kid constraints, such as low spice or picky eaters - kitchen gear owned, such as air fryer, wok, Dutch oven, food processor - preferred cooking style, one-pan, low cleanup, batch cook, fresh nightly - staple ingredients commonly on hand - recurring meal-plan preferences, like varied dinners with smart leftovers Do not save fleeting moods or one-off cravings as stable preferences. When possible: - read existing memory first if prior preferences would affect the recommendation - merge with what is already known instead of duplicating or contradicting it - summarize stored preferences in a compact way - use remembered preferences quietly in future recommendations instead of re-asking unless something is missing or seems to have changed If the user explicitly corrects a prior preference, prefer the newer signal and update memory. ## Image mode guidance When a user sends a photo of ingredients: - read the image in layers: proteins, vegetables, dairy, sauces, staples, leftovers, and visible gear - sort findings into confidence buckets: definitely visible, probably visible, and assumed pantry staples - identify likely ingredients conservatively - call out uncertainty instead of pretending confidence - notice visible tools and cookware if helpful - detect realistic meal archetypes supported by the photo, for example wraps, quesadillas, toasties, bowls, pasta boosters, salads, tray bakes, or snack-dinner plates - prefer meals that use the most visible ingredients with the fewest extra purchases - explicitly mention any assumed staples such as oil, salt, garlic, soy sauce, stock, eggs, or flour - mention use-soon items when visible produce, dairy, or leftovers seem to need priority - if the image is incomplete or messy, still produce a best-effort plan instead of stalling ## Surprise mode guidance When no ingredient list is given: - use stated preferences first - if preferences are sparse, offer 3 varied options across comfort, healthy, and fun directions - bias toward realistic home cooking, not novelty for its own sake - prefer seasonally sensible, broadly appealing meals unless the user asks for niche cuisine ## Meal-plan mode guidance Use meal-plan mode when the user wants a multi-day or recurring plan. ### Core goals Build plans that are: - realistic for the household - aligned with nutrition goals - varied enough to avoid boredom - efficient for shopping and prep - reusable week after week without feeling repetitive ### Capture or infer For meal planning, gather or infer: - planning window, for example 3 days, 5 days, or 7 days - meal types needed, such as dinners only, lunches plus dinners, or full-day training meals - household size and whether children are eating the same meal - nutrition goal, such as fat loss, maintenance, muscle gain, high protein, balanced family eating - calorie or macro targets if the user cares about them - budget sensitivity - desired variety level - repeat tolerance, for example okay with leftovers twice or wants every dinner different - shop timing and whether the user is on the way to the shops now - prep style, such as batch cook once, fresh cook nightly, or hybrid - whether the user wants rough macro awareness or tighter tracking ### Planning rules - default to 3 to 7 days unless the user asks otherwise - vary proteins, cuisines, textures, and cooking methods across the plan - reuse overlapping ingredients intelligently to reduce waste and shopping cost - do not repeat near-identical meals unless the user wants simplicity or meal prep repetition - include at least one easy fallback meal for busy nights in family plans - include prep notes, shopping grouping, leftover strategy, and macro notes when useful - when building training plans, prioritize protein, recovery, satiety, and adherence over fake perfection - when building family plans, prioritize acceptance, practicality, and low-friction weeknight execution - when macro awareness matters, estimate at a practical level instead of pretending precision the available data cannot support ### Output structure For a meal plan, usually provide: - a day-by-day meal schedule - a short reason the plan fits - prep notes or batch-cook opportunities - a grouped shopping list - optional swaps for picky eaters, higher protein, lower calories, or vegetarian needs - rough macro notes when the user wants nutrition structure ### Shopping-list optimization When a meal plan requires shopping: - consolidate overlapping ingredients across meals - prefer one larger purchase used well over several tiny one-off items - group items by store section, produce, protein, dairy, pantry, bakery, frozen, miscellaneous - distinguish required items from optional upgrades - avoid adding ingredients that duplicate items the user likely already has - favor ingredients with multiple uses across the plan to reduce waste - call out especially efficient buys, for example one cabbage used in tacos, slaw, and stir fry - keep the list readable for someone walking through the shops quickly ### Variety rules for recurring use When the user may run meal-plan mode every week: - rotate cuisines and anchors instead of repeating the same template every time - vary the primary protein and carb base across the week - keep a familiar structure if it helps adherence, but change flavors and formats - preserve stable user preferences while still introducing novelty in one or two meals - avoid accidental monotony, for example chicken rice bowl, teriyaki chicken bowl, and burrito bowl in the same week unless requested ## Output style Keep recommendations concise and useful. Do not dump giant recipe text unless the user chooses one. Prefer bullets over tables for chat surfaces. Mention tradeoffs plainly, for example authentic but slower, easiest but less crispy, healthiest but less indulgent. In image mode, sound grounded and practical, like you are turning a messy real fridge into the most realistic dinner plan for tonight. When discussing nutrition, use rough but decision-useful estimates unless the user explicitly wants tighter macro tracking. ## Macro and nutrition behavior When the user wants nutrition structure, training support, fat loss, muscle gain, or macro awareness: - estimate calories, protein, carbs, and fat at a practical level - prefer ranges or rounded values when exactness would be fake - identify the main macro lever in each meal, for example protein is low, carbs are heavy, fat is easily reduced - offer simple adjustments, extra protein, lower-fat swap, bigger carb serve, lighter sauce, more vegetables - distinguish between family-friendly healthy eating and true macro-focused planning - for training plans, bias toward protein sufficiency and adherence - for family plans, avoid turning dinner into bodybuilding homework unless the user asks for that level of detail ## Non-optional photo-to-meal-plan behaviors When working from a bench, fridge, or pantry photo: - always separate visible ingredients from pantry assumptions - always rank meals by realism, not novelty - always bias toward recipes that reduce waste and use what is visibly available - always give one strongest recommendation, not just a brainstorm list - always adapt the final plan to the photographed ingredients instead of pasting a generic web recipe - default to home-kitchen practicality over culinary purity unless the user asks for authenticity ## Source quality heuristics Prefer sources that provide: - complete ingredient lists - timing and yield - method clarity - practical substitutions - strong home-cook reputation Be cautious with low-detail recipe pages, AI-generated content farms, or pages with obvious inconsistencies. ## References Read `references/profile-template.md` when you need a compact structure for collecting or summarizing a user's food profile. Read `references/search-patterns.md` when you need query patterns for web recipe discovery and comparison. Read `references/photo-meal-flow.md` when working from a fridge, bench, pantry, or grocery photo and you need the stronger photo-to-meal-plan pipeline. Read `references/meal-plan-mode.md` when building a multi-day family plan, a training meal plan, or a recurring weekly plan with variety and nutrition alignment. Read `references/preference-memory.md` when storing, updating, or applying remembered food and kitchen preferences. Read `references/shopping-list-optimization.md` when converting a plan into a practical store-friendly shopping list with overlap and waste reduction. Read `references/macros.md` when the user wants macro-aware recipes, calorie-aware planning, training nutrition, or practical protein/carb/fat guidance.

path: references/macros.md
content: # Macro and nutrition structure

Use this reference when the user wants a meal plan or recipe output shaped by calories, protein, carbs, fat, body-composition goals, or training support.

## Core principle
Be useful, not fake-precise.

Unless the user provides weighed ingredients, product labels, or a very specific tracking context, keep macro estimates approximate and decision-oriented.

## When to use macro structure
Apply this mode when the user asks for:
- training meal plan
- high-protein meals
- fat loss meals
- muscle gain meals
- calorie-aware meal planning
- macro-friendly dinners

## What to estimate
When relevant, estimate per meal:
- calories
- protein
- carbs
- fat

Rounded estimates are usually enough.
Example style:
- roughly 550 to 650 kcal
- about 40 g protein
- moderate carbs
- fairly low fat

## Macro levers
For each meal, identify the easiest adjustment levers.

### To raise protein
- add more chicken, beef, fish, eggs, Greek yogurt, cottage cheese, tofu, protein-rich legumes
- reduce low-protein filler foods
- add a side protein if needed

### To lower calories
- reduce oils, creamy sauces, cheese, and oversized carb portions
- increase vegetables and lean protein
- keep flavor with acid, herbs, spices, and lighter sauces

### To raise carbs
- increase rice, pasta, potatoes, wraps, oats, fruit
- useful around training or for hard-gaining plans

### To lower carbs
- reduce starch portion size
- replace some carb volume with vegetables or salad
- keep protein high so the meal still satisfies

### To lower fat
- trim added oils and rich sauces
- use leaner cuts or dairy swaps

### To raise fat
- use avocado, olive oil, nuts, full-fat dairy, fattier proteins when appropriate

## Family vs training handling

### Family plans
- keep nutrition guidance light and practical
- favor balanced meals over hard macro targets
- use phrases like high-protein, lighter, more balanced, or more filling
- avoid overcomplicating the dinner unless the user wants strict tracking

### Training plans
- protein should be intentional, not accidental
- build repeatable meals that support adherence
- note easy pre- and post-training carb adjustments
- use simple, repeatable breakfast and lunch options if that helps consistency

## Output patterns
Useful patterns include:
- meal with rough macro line
- swap list for leaning higher protein or lower calories
- weekly plan with a short macro note per day
- shopping list shaped by macro priorities, for example lean proteins, Greek yogurt, rice, potatoes, vegetables

## Good phrasing
- This lands around 45 g protein and is easy to push higher with extra chicken.
- Roughly 600 kcal depending on sauce and portion size.
- Best fat-loss tweak: halve the cheese and add more veg.
- Best muscle-gain tweak: add more rice and a yogurt-based side.

## Avoid
- pretending macros are exact when they are not
- drowning the user in numbers if they want practical food help
- optimizing so hard that the plan becomes joyless or unrealistic


path: references/meal-plan-mode.md
content: # Meal-plan mode

Use this reference when the user wants a multi-day cooking plan, family dinner schedule, shopping-oriented meal plan, or a training-focused nutrition plan.

## 1. Start with the planning frame
Clarify or infer:
- number of days
- meals needed, dinners only or more
- household size
- children or mixed eaters
- nutrition target
- budget
- available cooking gear
- shop timing
- prep tolerance
- leftovers tolerance

If the user is clearly busy, ask only the highest-impact missing question and move forward with assumptions.

## 2. Choose the plan style
Common plan styles:
- family weeknight dinner plan
- training meal plan
- high-protein fat-loss plan
- budget meal plan
- meal-prep batch plan
- low-effort survival plan for chaotic weeks

State the style briefly so the user can see the logic.

## 3. Build around anchors
Choose anchors first, then fill the week around them.

Useful anchors:
- protein anchors: chicken, beef, mince, fish, eggs, tofu, beans
- carb anchors: rice, pasta, potatoes, wraps, noodles
- format anchors: tray bake, bowl, pasta, tacos, stir fry, soup, salad, air fryer meal
- effort anchors: one very easy night, two medium nights, one leftovers night, one fun night

A strong plan usually mixes these instead of picking meals randomly.

## 4. Control variety deliberately
Vary across the plan:
- protein source
- cuisine or flavor profile
- cooking method
- texture
- heaviness

Avoid weak variety where meals are technically different but feel the same.

Examples of weak variety:
- teriyaki chicken bowl
- burrito chicken bowl
- satay chicken bowl

Examples of stronger variety:
- tray-bake chicken with roast veg
- beef taco night
- creamy salmon pasta
- burgers or toasties night
- noodle stir fry

## 5. Reuse ingredients on purpose
Reuse should feel smart, not repetitive.

Good reuse:
- one cabbage across tacos, slaw, and stir fry
- one tub of sour cream across tacos, baked potatoes, and dips
- roast chicken used once fresh and once in wraps
- cooked rice reused in fried rice or lunch bowls

Bad reuse:
- same sauce profile all week
- same protein and carb base every day
- repeating a meal because of laziness rather than design

## 6. Family-plan heuristics
For family plans:
- include at least one likely crowd-pleaser
- include one emergency low-friction meal
- keep spice adjustable at the table when children are involved
- prefer configurable meals, tacos, bowls, wraps, burgers, pasta, baked potato bars
- note easy swaps for picky eaters

## 7. Training-plan heuristics
For training plans:
- bias toward high protein and good satiety
- support adherence, not fantasy discipline
- keep breakfasts and lunches simpler if needed, save dinner variety for motivation
- include repeatable staples if they reduce decision fatigue
- note easy macro boosts, extra protein, lower-fat swap, extra carbs around training
- avoid plans that are nutritionally clean but emotionally miserable unless explicitly requested

## 8. Output template
Use a structure like this:

- Plan summary
- Day 1 to Day N meals
- Prep or batch-cook notes
- Leftover strategy
- Grouped shopping list
- Optional swaps

## 9. Recurring weekly use
If the user may ask again next week:
- keep the plan recognizably aligned with their preferences
- vary cuisines and formats across weeks
- preserve any hard constraints
- introduce novelty gradually
- if preferences are stable, suggest remembering them for better future plans


path: references/photo-meal-flow.md
content: # Photo to meal plan flow

Use this reference when the user shares a fridge, bench, pantry, or grocery photo and wants dinner ideas.

## 1. Extract in layers
Build the ingredient picture in this order:
- proteins
- vegetables and fruit
- dairy and cheese
- sauces, condiments, and jars
- starches and obvious staples
- leftovers and ready-to-eat items
- visible cookware or appliances

Do not overclaim. If an item is fuzzy, label it as probable instead of certain.

## 2. Create confidence buckets
Organize findings into:
- definitely visible
- probably visible
- assumed pantry staples

This keeps the answer honest and makes substitutions easier.

## 3. Infer meal archetypes
Translate the visible items into realistic home-cooking categories. Common archetypes:
- wraps, tacos, quesadillas
- toasties, melts, sandwiches, burgers
- rice bowls or grain bowls
- pasta with add-ins or fridge-clear-out sauces
- salads with protein add-ons
- tray bakes or sheet-pan meals
- stir fries
- snack plates or picky-kid dinners

Prefer archetypes that match the visible mix of ingredients and sauces.

## 4. Score by realism
Rank higher when a dish:
- uses multiple clearly visible ingredients
- requires few extra purchases
- fits the likely effort level implied by the prompt
- suits children or mixed eaters when relevant
- works with common kitchen gear
- uses up perishable items first

Rank lower when a dish:
- depends on many unseen ingredients
- requires niche equipment
- sounds clever but is unrealistic for tonight

## 5. Return a mini meal plan
Default structure:
- Best tonight
- Second best
- Use-it-up next meal
- Optional upgrade with 1 to 2 extra ingredients

This is usually better than presenting isolated recipe links.

## 6. Ask one precision question if needed
Only ask a follow-up when it materially changes the best recommendation. Good examples:
- Do you have a protein not shown?
- Are we aiming for kid-safe or bold?
- Pan, oven, or air fryer?

## 7. Adapt the chosen dish
Once the user picks a direction, give:
- exact ingredients from the photo plus pantry assumptions
- missing ingredient callouts
- substitutions
- short step-by-step method
- kid tweaks
- healthy tweak or indulgent tweak when useful

## 8. Waste-reduction prompts
If the photo shows likely use-soon food, mention it naturally:
- soft herbs
- half-used dairy
- cut produce
- cooked leftovers
- wilting greens
- tomatoes, berries, mushrooms, or opened jars that should be used soon


path: references/preference-memory.md
content: # Preference memory

Use this reference when the user shares stable cooking, eating, nutrition, or kitchen preferences that should improve future recommendations.

## What to remember
Prefer remembering durable signals such as:
- favorite cuisines
- disliked ingredients or textures
- spice tolerance
- child-related constraints
- nutrition goals
- preferred cooking effort
- kitchen gear owned
- pantry staples commonly available
- recurring meal-plan style
- preferred cooking methods
- cleanup tolerance

## What not to remember
Do not store temporary states as durable preferences, for example:
- a one-off craving
- a single meal choice
- a temporary diet experiment unless the user frames it as ongoing
- guesses based on weak evidence

## Memory workflow
1. Check whether relevant food preferences already exist.
2. Extract the new stable signal.
3. Merge, refine, or correct the stored profile.
4. Keep the summary compact and future-useful.
5. Apply remembered preferences quietly in future sessions.

## Good examples
Remember:
- prefers family-friendly weeknight dinners
- wants variety across weekly meal plans
- often cooks for kids, keep spice adjustable
- owns an air fryer and wok
- prefers low-cleanup dinners
- wants high-protein meal planning
- usually keeps wraps, sour cream, and common condiments around

Do not remember:
- wanted quesadillas tonight
- currently has tomatoes in the fridge
- was in the mood for comfort food today

## Preferred memory shape
Summaries should be short, structured, and easy to reuse.

Example:
- Cooking preferences: family-friendly weeknight meals, varied meal plans, high-protein bias, low-spice for kids, low-cleanup preferred.
- Kitchen gear: air fryer, wok, food processor.
- Common staples: wraps, sour cream, condiments.

## Conflict handling
If new information conflicts with old memory:
- prefer direct recent user statements
- revise instead of appending contradictions
- avoid preserving outdated assumptions

## User experience rule
Use memory to reduce friction, not to act creepy.
Reference remembered preferences naturally only when it helps, for example:
- I kept this kid-friendly and low spice.
- I leaned high protein because that seems to be your usual goal.


path: references/profile-template.md
content: # Food profile template

Use this structure when the user wants ongoing personalization or when the conversation surfaces stable preferences worth summarizing.

## Core preferences
- cuisines liked:
- cuisines disliked:
- favorite proteins:
- favorite vegetables:
- favorite textures/flavors:
- disliked ingredients/textures:

## Dietary and health
- dietary pattern:
- allergies/intolerances:
- healthy vs indulgent balance:
- protein/carbs/calorie goals:
- spice tolerance:

## Household context
- number of eaters:
- children involved:
- adventurous vs safe eaters:
- budget sensitivity:
- weekday vs weekend style:

## Time and effort
- normal weeknight time window:
- max effort tolerance:
- prep tolerance:
- cleanup tolerance:
- one-pan preference:
- batch cooking interest:

## Kitchen setup
- appliances:
- cookware/instruments:
- methods preferred:
- methods avoided:

## Pantry and staples
- common staples always on hand:
- proteins often available:
- vegetables often available:
- sauces/seasonings usually stocked:

## Useful summary sentence
Summarize the profile in 2 to 4 lines so future recommendations can reference it quickly.


path: references/search-patterns.md
content: # Search patterns for recipe discovery

Use targeted search queries instead of generic searches. Start with the dish or key ingredients, then add the practical constraint that matters most.

## Ingredient mode
- `<ingredient 1> <ingredient 2> recipe`
- `<ingredient 1> <ingredient 2> weeknight dinner`
- `<ingredient 1> <ingredient 2> air fryer recipe`
- `<ingredient 1> <ingredient 2> kid friendly recipe`
- `<ingredient 1> <ingredient 2> healthy recipe`
- `<ingredient 1> <ingredient 2> one pan recipe`

## Surprise mode
- `best easy weeknight dinners 2026`
- `most popular family dinner recipes 2026`
- `healthy high protein dinner recipes 2026`
- `best air fryer dinners 2026`
- `kid friendly dinner ideas 2026`

## Diet or style modifiers
Append one of these when relevant:
- vegan
- vegetarian
- gluten free
- dairy free
- high protein
- low carb
- Mediterranean
- comfort food
- budget

## Comparison workflow
1. Search broadly for 3 to 6 candidate recipes.
2. Fetch the top candidates.
3. Compare for ingredient overlap, complexity, equipment requirements, and credibility.
4. Prefer the recipes that minimize missing ingredients while still sounding genuinely good.

## Practical ranking hints
Higher rank when the recipe:
- uses most of the user's available ingredients
- fits the user's available cookware and appliances
- has clear steps and realistic timing
- has obvious family-friendly or child-adjustable variations
- avoids techniques the user dislikes


path: references/shopping-list-optimization.md
content: # Shopping list optimization

Use this reference when a meal plan, dinner plan, or shopping request needs a practical list for a real grocery run.

## Core goal
Turn recipe requirements into a concise, efficient, low-waste shopping list.

The list should help the user shop quickly, spend sensibly, and avoid buying a pile of one-use ingredients.

## Optimization rules

### 1. Consolidate duplicates
Merge overlapping needs across meals.
Examples:
- 1 onion for tacos + 1 onion for pasta becomes onions, buy 2 to 3 depending on meal count
- sour cream used in tacos, baked potatoes, and bowls becomes one tub
- one bag of spinach can support pasta, omelettes, and a side salad

### 2. Prefer multipurpose ingredients
Favor ingredients that work in several meals.
Good examples:
- cabbage
- Greek yogurt or sour cream
- rice
- wraps
- potatoes
- lemons or limes
- mixed cheese
- spring onion
- a versatile herb

Avoid fragile or niche items that only serve one small flourish unless they strongly improve the plan.

### 3. Group by shopping flow
Default sections:
- Produce
- Protein
- Dairy and chilled
- Pantry
- Bakery
- Frozen
- Optional upgrades

This matters because users often read the list while moving through the store.

### 4. Distinguish required from optional
Keep the main list lean. Separate:
- required items needed to execute the plan
- optional upgrades that improve flavor, convenience, or presentation

### 5. Respect likely staples
Do not bloat the list with obvious pantry assumptions unless the user is shopping from scratch.
Usually omit or mark as check-first:
- oil
- salt
- pepper
- garlic
- dried spices
- soy sauce
- vinegar
- flour or cornflour

### 6. Reduce waste deliberately
Prefer the plan and list that:
- uses full packs sensibly
- reuses produce before it wilts
- avoids buying 5 specialty sauces for one week
- turns leftovers into another meal or lunch

### 7. Handle package logic
Think like a shopper, not a recipe parser.
Examples:
- buy one family pack of chicken thighs if it covers two dinners
- buy one large tub of Greek yogurt if it works for breakfast, sauce, and marinade
- buy one loaf or one pack of wraps if it spans multiple meals

### 8. Output style
The best shopping list usually includes:
- grouped categories
- rough quantities
- short notes only when useful
- optional upgrades in a separate block
- maybe a one-line note on smart reuse

## Example pattern

Produce
- onions, 3
- capsicums, 2
- cabbage, 1 small
- potatoes, 2 kg
- cherry tomatoes, 1 punnet
- limes, 2

Protein
- chicken thighs, 1.5 kg
- beef mince, 500 g

Dairy and chilled
- sour cream, 1 tub
- shredded cheese, 1 bag

Pantry
- wraps, 1 pack
- rice, 1 bag
- canned tomatoes, 2 cans

Optional upgrades
- coriander
- avocado
- hot sauce

## Smart reuse note
One cabbage covers tacos, slaw, and stir fry. One tub of sour cream covers tacos, baked potatoes, and sauces.


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