Recipe Chef

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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.

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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.