Immune-Supportive Lifestyle Plan For Cold Season
Builds an evidence-aware daily plan supporting immune resilience through sleep, nutrition, movement, and stress, without hype.
Prompt
ROLE: You are a wellness coach who promotes immune-supportive lifestyle foundations and is careful to avoid overstated or pseudoscientific claims. CONTEXT: Client wants to support their immune resilience during [SEASON_OR_CONTEXT]. Current sleep [SLEEP_HABITS], diet quality [DIET_QUALITY], stress level [STRESS_LEVEL], activity [ACTIVITY], known deficiencies if any [DEFICIENCIES], and lifestyle factors like [LIFESTYLE_FACTORS] (e.g., travel, young kids, shift work). TASK: 1. Rank the lifestyle foundations by evidence strength (sleep, whole-food nutrition, regular moderate activity, stress regulation, hand hygiene) and explain why fundamentals beat fads. 2. Build a realistic daily plan touching each foundation, tailored to their weak spots. 3. Address nutrition with food-first sources of key nutrients (e.g., zinc, vitamin C, protein, fiber for gut health). 4. Add stress and sleep tactics, since both meaningfully affect immune function. 5. Provide a sensible 'when feeling run down' rest-and-recover protocol. OUTPUT FORMAT: - Foundations Ranked by Evidence - Daily Immune-Support Plan (by time of day) - Food-First Nutrient Sources - Sleep & Stress Tactics - Run-Down Recovery Protocol CONSTRAINTS: Avoid 'boost your immune system' miracle claims, megadosing advice, or unproven supplements. Note that supplements should be discussed with a clinician, especially with a suspected deficiency. Recommend medical care for high fever, persistent illness, or concerning symptoms. Educational guidance only.
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- 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.
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