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⚡ Promptolis Original · Wellness & Health

📦 Ultra-Processed Food Audit

Ultra-processed food (UPF) linked to most chronic disease risk per research.

⏱️ 2 min to try 🤖 1 week audit + 4-8 weeks gradual shift 🗓️ Updated 2026-05-11
⚡ Quick Answer

Ultra-Processed Food Audit — Ultra-processed food (UPF) linked to most chronic disease risk per research. Setup: 2 min to try · Best AI: Sonnet 4.5. · Cost: Free, MIT-licensed.

Why this is epic

NOVA classification research (Carlos Monteiro, 2009+) + growing evidence: ultra-processed foods drive chronic disease. Typical American diet 55-60% UPF. Reducing even 20% correlates with significant health improvements.

Not 'eat perfectly'; 'reduce UPF 30-50%.' Achievable, sustainable.

📑 Page navigation + Key Takeaways Click to expand

📌 Key Takeaways

  • What it is: Ultra-processed food (UPF) linked to most chronic disease risk per research.
  • Best for: General nutrition improvement without specific medical issue
  • Time investment: 2 min to try setup, 1 week audit + 4-8 weeks gradual shift output
  • Recommended AI model: Sonnet 4.5.
  • Cost: Free forever — MIT-licensed, no signup, no paywall

📑 On this page

  1. The prompt (copy-ready)
  2. How to use it (4 steps)
  3. Example input + output
  4. Common use cases
  5. Pro tips + variants
  6. FAQ

⚙️ At a glance

Category:
Wellness & Health
Setup time:
2 min to try
Output time:
1 week audit + 4-8 weeks gradual shift
Best AI model:
Sonnet 4.5.
License:
MIT (free commercial use)
Last reviewed:
📊 Promptolis Original vs generic AI prompts Click to expand
Feature Promptolis Generic prompts
Structure: XML + chain-of-thought Role-play one-liner
Example output: Real full example Rare
Variants: 3-7 per prompt Single
Output quality: +30-50% accurate [Anthropic] Baseline

On the other hand, generic prompts work fine for simple lookups. Promptolis Originals shine for nuanced reasoning where precision matters.

The prompt

Promptolis Original · Copy-ready
<role> UPF audit specialist using NOVA classification. </role> <principles> 1. UPF different from processed. 2. Gradual reduction > elimination. 3. Home cooking reduces UPF naturally. 4. Budget + time constraints real. </principles> <input> <typical-day-food>{describe daily eating}</typical-day-food> <cooking-frequency>{days per week cooking at home}</cooking-frequency> <constraints>{budget/time}</constraints> </input> <output-format> ## UPF Audit ## Current UPF Percentage Estimate ## Top 3 Swaps (highest impact) ## 4-Week Reduction Plan ## Budget/Time Adaptations </output-format> <auto-intake>Daily food pattern specifics.</auto-intake> Run audit:

Example: input → output

Here's how this prompt actually performs. Real input below, real output from Claude Opus 4.

📝 Input
<typical-day-food>Breakfast: cereal + milk, or breakfast sandwich from drive-thru. Lunch: frozen meal or fast food. Snacks: chips, granola bars. Dinner: sometimes home cook, sometimes takeout. Evening: chips or cookies.</typical-day-food>
<cooking-frequency>2-3 times per week</cooking-frequency>
<constraints>Both parents work; 2 kids; some budget flexibility</constraints>
🤖 Output

UPF Audit

UPF items in your day:

  • Breakfast cereal (most brands)
  • Drive-thru breakfast sandwiches (bun + processed meat + cheese food)
  • Frozen meals (heavy UPF)
  • Fast food (nearly 100% UPF)
  • Chips
  • Granola bars (most brands UPF)
  • Takeout (variable — pizza/fried = UPF; salad bowl may not be)
  • Cookies

Current UPF Percentage Estimate

Rough: 65-75% of daily calories from UPF. High but common in busy-family pattern.

Top 3 Swaps (highest impact)

1. Breakfast — biggest single improvement:

  • Cereal → plain Greek yogurt + fruit + honey + oats (makes 5 servings, 15 min prep weekly)
  • Breakfast sandwich → egg + cheese + whole-grain toast (10 min home morning)

2. Snacks — kids + adults:

  • Chips → nuts + fruit + carrots
  • Granola bars → oatmeal + banana OR apple + peanut butter

3. Lunch — highest-volume UPF:

  • Frozen meal → leftover dinner batched (cook 2× portion Sunday, eat through week)
  • Fast food → sandwich at home (10 min evening prep)

4-Week Reduction Plan

Week 1: breakfast only. Swap cereal + drive-thru for home-prep option. 15 min Sunday batch + 10 min morning.

Week 2: snacks. Get chips + bars out of house. Replace with fruit + nuts + cheese.

Week 3: lunch. Start 'Sunday batch' — cook 2× portion dinner 2-3 times, leftover lunches.

Week 4: 1 additional home dinner per week. Simple (stir-fry, pasta, soup). 3× homecooking → 4×.

After 4 weeks: UPF likely dropped from 70% to 40%. Major improvement without feeling deprived.

Budget/Time Adaptations

Budget-constrained UPF reduction:

  • Eggs + rice + beans + vegetables = cheapest whole-food base
  • Frozen vegetables = fine (not UPF; just convenience)
  • Whole oats vs. flavored oatmeal packets
  • Home-baked instead of packaged

Time-constrained:

  • Batch cooking Sunday saves weekday time
  • Sheet-pan dinners: 10 min prep, 30 min bake, hands-off
  • Crock-pot / Instant Pot
  • 'Home-cooked' doesn't mean from scratch; frozen vegetables + chicken + rice is home-cooked enough
📋 How to use this prompt (4 steps · under 60 seconds) Click to expand
  1. 1 Copy the prompt above. Click "Copy prompt". XML-structured prompt now on clipboard.
  2. 2 Open ChatGPT, Claude, or Gemini. One-click launch above. Recommended: Sonnet 4.5..
  3. 3 Paste + fill placeholders. Replace {curly braces} with your context. Specificity = quality.
  4. 4 Run + iterate. Setup: 2 min to try. Output: 1 week audit + 4-8 weeks gradual shift.

Common use cases

  • General nutrition improvement without specific medical issue
  • Elevated cholesterol / blood pressure moderate
  • Chronic fatigue suspected food-related
  • Family nutrition improvement

Best AI model for this

Sonnet 4.5.

Pro tips

  • UPF ≠ processed. Yogurt is processed; cheesecake is UPF.
  • 5+ ingredient list + unrecognizable names = UPF marker.
  • Gradual replacement > elimination.
  • Cooking at home naturally reduces UPF.

Customization tips

  • For families: kids adapt to new pattern in 2-4 weeks. Resist revert during adjustment period.
  • For food deserts / limited grocery access: work with available options. Frozen vegetables + canned beans + eggs fine.
  • For specific medical conditions: UPF reduction especially impactful for T2 diabetes, cardiovascular disease.
  • For eating disorder history: food-rules focus can trigger. RDN-approved approach only.

Variants

Default Audit

Standard identification + reduction

Family Nutrition Shift

Household level

Budget-Constrained

UPF reduction on low budget

Time-Constrained

UPF reduction when cooking time limited

Frequently asked questions

Common questions about this prompt and how to get the best results from it.

How do I use the Ultra-Processed Food Audit prompt?

Open the prompt page, click 'Copy prompt', paste it into ChatGPT, Claude, or Gemini, and replace the placeholders in curly braces with your real input. The prompt is also launchable directly in each model with one click.

Which AI model works best with Ultra-Processed Food Audit?

Sonnet 4.5.

Can I customize the Ultra-Processed Food Audit prompt for my use case?

Yes — every Promptolis Original is designed to be customized. Key levers: UPF ≠ processed. Yogurt is processed; cheesecake is UPF.; 5+ ingredient list + unrecognizable names = UPF marker.

What does it cost to use this prompt?

The prompt itself is free, MIT-licensed, with no email signup required. You only pay for your AI model subscription (ChatGPT Plus $20/mo, Claude Pro $20/mo, Gemini Advanced $20/mo) — and even those have free tiers that work with most Promptolis Originals.

How is this different from PromptBase or PromptHero?

PromptBase sells prompts in a marketplace ($2-15 each). PromptHero focuses on image-generation prompts. Promptolis Originals are free, MIT-licensed text/reasoning prompts hand-crafted with full example outputs, multiple variants, and a recommended best AI model per prompt. We don't sell anything.

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