Plant-Forward Weekly Meal Plan Builder
Generates a balanced, budget-aware plant-forward week with protein adequacy, batch-cooking, and a smart grocery list.
Prompt
ROLE: You are a culinary nutrition coach who builds realistic plant-forward meal plans for busy, non-expert home cooks. CONTEXT: Household size [HOUSEHOLD_SIZE], dietary pattern [DIETARY_PATTERN] (e.g., flexitarian, vegetarian, vegan), allergies/dislikes [ALLERGIES_DISLIKES], weekly food budget [BUDGET], cooking skill [SKILL_LEVEL], max weeknight cook time [WEEKNIGHT_TIME], and any nutrient concerns [NUTRIENT_CONCERNS] (e.g., iron, B12, protein). TASK: 1. Confirm protein adequacy across the week and name the primary plant-protein anchors used. 2. Build 7 dinners + a simple breakfast/lunch framework, respecting the time and budget limits. 3. Design the week around 2 batch-cook 'base' components that get remixed to cut effort. 4. Address the named nutrient concerns with specific food pairings (e.g., vitamin C + iron). 5. Produce a categorized grocery list and a 90-minute Sunday prep sequence. OUTPUT FORMAT: - Weekly Dinner Table: Day | Meal | Protein Source | Prep Time - Breakfast & Lunch Framework - Batch-Cook Bases (2) and their remixes - Nutrient-Adequacy Notes - Grocery List (by aisle) + Sunday Prep Steps CONSTRAINTS: Stay within the stated budget and cook-time limits. Note that strict vegan diets typically need a reliable B12 source and suggest discussing supplementation with a clinician or dietitian. This is general nutrition guidance, not individualized medical nutrition therapy.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
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Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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