by Calorie IQ (LX AI)
Start with a personal daily target and a sample day. Adjust with real meals — avoid fabricating adherence metrics.
I built Calorie IQ to give you a clear daily number for calories and macros without opening a spreadsheet. You enter four things (goal, current weight, activity level, and diet preferences) and the studio drafts a personal target alongside a one-day sample sketch. The sample is not a prescription. It's a starting point you can hold up against what you actually eat.
A full day of meals shows you what portions and food choices actually hit the target. Compare the sample with your real meals and you'll see where you're running over or under. That feedback loop is faster than logging every gram in a sheet.
The weekly view is a habit, not another screen. Re-run the studio when your weight, goal, or activity changes and keep the drafts side by side. Over a week you can spot patterns, like protein falling off on weekends, without doing any math.
There's no hidden equation and no fine-tuned model. Deterministic checks run first to confirm your inputs are usable, then a model-assisted narrative drafts the daily calorie figure and a macro split from your goal, weight, and activity level.
The output leads with the drafted daily calories and grams of protein, carbs, and fat, followed by the one-day sketch and the rule checks that ran. Portions are suggestions in plain language, not weighed servings.
The sample day is a drafted sketch: a protein source, a carbohydrate source, and a fat source for each meal, written to respect the restrictions you listed. It exists to make the target concrete, not to be followed to the gram.
If the draft says ~1,800 kcal with 140g protein, a matching day might look like: Greek yogurt with berries and oats for breakfast, a chicken salad with olive oil for lunch, a protein shake with almond butter as a snack, and salmon with quinoa and broccoli for dinner. Treat the numbers as a sketch you can swap item for item with a similar profile.
The sketch shows one way to approach the target. Swap any item for a similar macro profile and stay in range. The tool re-drafts when you change inputs.
The weekly view is a simple habit: re-run the studio when something changes and keep the drafts. You compare targets across the week instead of logging every gram.
Daily logging can feel like a chore, and plenty of people burn out on it. A weekly check-in gives you enough data to spot trends without chasing perfection. You still learn which meals need tweaking, but you spend far less time entering data.
Calorie IQ lets you list foods you avoid in the diet preferences field, and the drafted sample day respects that list. Common restrictions include gluten free, dairy free, vegetarian, vegan, nut free, and low FODMAP.
Because the draft works with macro totals, swapping foods doesn't change the calorie or macro goal. The only thing that changes is the specific ingredients you see in the sample. You can keep the same portion sizes or adjust them to match your taste.
A few limits worth stating plainly. This is not a guarantee that you'll reach any specific weight change. It doesn't promise 100% accuracy in macro counting, because food labels have variance and cooking methods alter nutrients. It will never replace medical advice from a doctor or dietitian. If you have a health condition that requires a strict diet, talk to a professional before relying on any automated plan.
The sample day is a starting point, not a meal plan you have to follow forever. Ignore it, edit it, or use it as inspiration. Re-running with clearer preferences is the intended way to iterate, not a sign something broke.
Yes. It provides a one-day sample meal plan and a progress-friendly weekly view.
It adapts to diet restrictions when you set them.
No. The point is to skip spreadsheets and guesswork with a clear target and simple plan.
Anyone who wants a personalized daily target and a simple plan without manual tracking or a coach.
Want to try the product? Calorie IQ
Generated 2026-09-17 · primary sources only · no fabricated traffic metrics