Daily Habit Scorecard

Track, score, and analyze your daily habits with streak counting, trend visualization, and accountability reports. This skill turns habit tracking into a data-driven practice -- you define your habits, log completions each day, and receive weekly trend analysis showing which habits stick, which ones slip, and what patterns predict success or failure. Integrates with Streaks, Habitica, Notion, Apple Health, and plain CSV for maximum flexibility.

Supported Platforms & Integrations

Platform	Setup Method	Auth Type	Notes
Streaks (iOS/macOS)	Shortcuts integration	Siri Shortcuts	Syncs completion status bidirectionally
Habitica	Habitica API v3	API token + user ID	Reads dailies and habits, syncs completions
Notion	Notion API	API token	Reads/writes to habit tracking database
Apple Health	HealthKit via Shortcuts	System permission	Reads step count, sleep, exercise data

When to Use This Skill

• Use this when you want to build or maintain multiple daily habits simultaneously
• Use this when you want data-driven insights about your habit consistency
• Use this when existing habit apps feel too gamified or too simple
• Consider alternatives when you track only one habit (a simple reminder suffices)

Quick Start

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# Minimal configuration - habit-scorecard.yml
skill: daily-habit-scorecard
habits:
  - name: "Morning exercise"
    target: daily
    category: health
    points: 2
  - name: "Read 30 minutes"
    target: daily
    category: learning
    points: 1
  - name: "No social media before noon"
    target: daily
    category: focus
    points: 1

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claude /daily-habit-scorecard

Expected Output

HABIT SCORECARD - Saturday, March 15, 2026
Day 34 of tracking | Current best streak: 18 days (Reading)

Check off completed habits today:

  [x] Morning exercise (2 pts)          Streak: 5 days
  [x] Read 30 minutes (1 pt)            Streak: 18 days
  [ ] No social media before noon (1 pt) Streak: BROKEN (was 8)
  [x] Drink 8 glasses water (1 pt)      Streak: 3 days
  [x] Journal before bed (1 pt)         Streak: 12 days
  [N/A] Deep work block (3 pts)         Weekend - not tracked

TODAY'S SCORE: 5/6 points (83%)

...

Advanced Configuration

Platform-Specific Setup

Habitica Sync

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sync: habitica
habitica:
  user_id_env: "HABITICA_USER_ID"
  api_token_env: "HABITICA_API_TOKEN"
  sync_dailies: true
  sync_habits: true
  map_habits:
    "Morning exercise": "habitica-daily-id-123"

Full Options Reference

Parameter	Type	Default	Description
habits	array	required	List of habit objects with name, target, points
schedule	string	"21:30"	Daily check-in time
scoring	string	"weighted"	Scoring: weighted (by points), equal, percentage
streak_tracking	boolean	true	Track consecutive completion streaks
weekly_report	boolean	true	Generate weekly trend analysis
monthly_report	boolean	true	Generate monthly deep analysis

Core Concepts

Concept	Purpose	How It Works
Weighted Scoring	Reflects habit importance	Higher-point habits (exercise: 3pts) count more than lower-point ones (water: 1pt)
Streak Psychology	Leverages loss aversion	Visual streak counters create "do not break the chain" motivation
Trend Analysis	Reveals behavioral patterns	Compares weekly averages over time to show improvement or decline trajectories
Day-of-Week Patterns	Identifies weak spots	Aggregates scores by day to find consistently low-performing days

Architecture

Habit Config ──> Check-in Interface ──> Completion Recorder ──> Score Calculator
                                                |                        |
  History DB ──> Streak Engine ─────────────────┘                  Trend Analyzer

Workflow Examples

Scenario 1: Building a morning routine from scratch

Input: 4 new morning habits, user has no existing streaks, day 1 Processing: Starts with lenient scoring (tracks but does not grade harshly for first 7 days), focuses on completion count over percentage, and sets initial streak targets at 3 days. Output: Encouraging first-week report showing completion count with "You showed up 5 out of 7 days -- that is a strong start" framing instead of "71% completion."

Scenario 2: Mid-quarter habit audit

Input: 90 days of tracking data across 6 habits, one habit at 25% completion Processing: Identifies the consistently-failed habit, analyzes what day/time it fails, checks if it correlates with other habit failures, and recommends either modifying, replacing, or dropping it. Output: Data-driven recommendation like "Deep work block completes 90% on Mon/Wed but 10% on meeting-heavy days. Consider making it Mon/Wed/Fri only instead of daily."

Best Practices

1. Start with 3-5 habits maximum -- Research shows tracking more than 7 habits simultaneously leads to decision fatigue and declining completion rates. Start with.

2. Assign points honestly based on difficulty -- Give harder habits more points. If exercise takes real willpower but drinking water is easy, reflect that in scoring (3 vs 1)..

3. Use the grace period for sustainability -- Setting grace_period to 1 means one missed day does not break your streak. This prevents the "I missed one day so the streak.

Common Issues

1. Forgetting to log habits before bed -- Set the schedule 30 minutes before your typical bedtime. Enable system notifications if your OS supports terminal alerts..

2. Apple Health data not auto-completing -- Ensure the Shortcuts integration has Health read permission. Some metrics (like water intake) require manual logging in the.

Privacy & Data Handling

All habit data is stored locally in ~/.claude/data/habit-scorecard/ as plain JSON and CSV files. No habit names, completion data, or behavioral patterns are transmitted to external services unless you explicitly enable Habitica, Notion, or Google Sheets sync. Health data from Apple Health stays on-device and is read but never stored or forwarded. Weekly reports sent via email use your local mail client.