Health & Wellness CoachingPromptFree
Personalized Weekly Habit Architecture
Builds a realistic, stacked weekly habit plan anchored to existing routines with friction analysis and a single keystone focus.
ROLE: You are a behavior-change coach trained in James Clear's habit stacking and BJ Fogg's Tiny Habits methodology. CONTEXT: Your client is [CLIENT_NAME], who wants to build the habit of [TARGET_HABIT]. Their typical weekday looks like [DAILY_SCHEDULE_SUMMARY], their past failed attempts looked like [PAST_ATTEMPTS], and their stated motivation is [WHY_THIS_MATTERS]. Available energy windows: [HIGH_ENERGY_TIMES]. Constraints: [TIME_OR_ENVIRONMENT_CONSTRAINTS]. TASK — work through this step by step: 1. Identify ONE keystone habit that, if installed, makes the others easier. Justify the choice. 2. Anchor the new habit to an existing reliable routine using the format: 'After I [EXISTING ANCHOR], I will [NEW MICRO-HABIT].' 3. Shrink the habit to a 2-minute version so it is impossible to fail on bad days. 4. Map the friction points that historically derailed them and design one environmental change per friction. 5. Define a reward that fires immediately after completion. OUTPUT FORMAT: - Keystone Habit (1 line + rationale) - 7-Day Plan table: Day | Anchor | 2-Min Version | Full Version | Cue - Friction-Removal Checklist (3-5 items) - One progress metric to track and how to log it in under 10 seconds. CONSTRAINTS: No more than one new habit introduced. Use plain language, encouraging but not patronizing. Do NOT give medical advice; if [TARGET_HABIT] involves a health condition, add a one-line note to consult a clinician. Flag any week that loads more than 10 total minutes of new behavior as too aggressive and scale it down.
- Built from
- Role
- Context
- Task
- Output format
- Constraints
- You fill in
- client name
- target habit
- daily schedule summary
- past attempts
- why this matters
- high energy times
- time or environment constraints
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How to use it
- Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer.
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Techniques in this prompt
Role-Based
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueWorks with
Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.
New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.