Analyze and Optimize Health Goals

Health Goal Analyzer runs eight capabilities against a user's stored health-goal data. It validates new goals against the SMART framework (Specific, Measurable, Achievable, Relevant, Time-bound), scoring each dimension 1-5 and producing an overall grade (S/A/B/C) with concrete examples of achievable pacing (weight loss at 0.5-1 kg/week, exercise 3-5 sessions of 30-60 minutes/week), via an algorithm like:

def validate_smart_goal(goal):
    scores = {
        'specific': check_specificity(goal),
        'measurable': check_measurability(goal),
        'achievable': check_achievability(goal),
        'relevant': check_relevance(goal),
        'time_bound': check_time_bound(goal)
    }
    overall = sum(scores.values()) / len(scores)
    grade = get_grade(overall)
    return scores, overall, grade

It tracks goal progress (completion percentage, time elapsed vs. target, average pace, and a four-tier rating from "excellent, ahead of schedule" to "severely behind"), analyzes habit formation through a five-stage model (days 1-7 initiation, 8-21 formation, 22-30 consolidation, 31-66 habit, 67+ automation) with streak and completion-rate statistics, tracks motivation on a 1-10 scale with phase-specific boost strategies (weeks 2-3 dip, months 1-2 fatigue, month 3+ burnout), manages a fixed achievement/badge system (goal- and habit-related badges like "21-Day Streak" or "Halfway There"), identifies barriers to goal achievement across five categories (time, motivation, environment, ability, physical) with a tailored recommendation per type, runs correlational analysis between a goal and other tracked health data (nutrition, exercise, sleep) using the Pearson correlation coefficient plus regression and trend-matching, and generates interactive HTML/ECharts reports - progress trend, habit heatmap, multi-goal comparison, motivation trend, or a combined comprehensive report - with dark/light theming, PDF export, and no internet dependency.

Use it to check whether a new health goal meets SMART criteria, track progress and habit continuity, correlate a goal with nutrition/exercise/sleep data, or get barrier-identification and motivation-management recommendations. Do NOT use it for medical diagnosis, treatment prescription, or as a substitute for professional medical advice, and do NOT use it to address eating disorders or compulsive behaviors - its own safety boundaries explicitly exclude all of these. It also runs built-in danger-signal checks - a weight-loss goal over 1 kg/week, a weight-gain goal over 0.5 kg/week, calorie restriction under 1200/day, exercise over 2 hours/day for 7 days a week, a completion rate under 30% for three consecutive weeks, or a motivation score under 3 for two consecutive weeks - and responds to these with a referral recommendation (a doctor, a specialist, a nutritionist, or a fitness trainer as appropriate) rather than acting on them directly.

Inputs are local JSON files: a main goal tracker (data-example/health-goals-tracker.json), daily log files (data-example/health-goals-logs/YYYY-MM/YYYY-MM-DD.json), and correlated health data from other trackers (nutrition, fitness, etc.). Outputs are a Markdown goal-analysis report (SMART scores, progress percentage, habit streaks, motivation status, correlation findings, barriers, unlocked achievements, and next steps) or an interactive HTML report built with ECharts 5.x, covering progress trends, a habit-completion heatmap, multi-goal comparison, and motivation trends.

Restricted to Read, Grep, Glob, and Write tools with no external API calls; cross-references other locally stored health-tracking modules (nutrition, fitness) for its correlational analyses, and renders reports client-side with the ECharts 5.x library loaded from CDN.

Anyone managing personal health goals locally who wants a structured SMART-goal check, progress and habit tracking, and correlation with their other health data, without the tool making medical or diagnostic claims.