xint
X Intelligence CLI — search, monitor, analyze, and engage on X/Twitter. TypeScript + Bun. AI agent skill.
Personal accountability system for the Lofy AI assistant — morning briefings, evening reviews, weekly reports, goal tracking, habit monitoring with streak counting, and adaptive nudge logic. Use when managing daily routines, life goals, habit streaks, or delivering scheduled briefings and reviews.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install harrey401/lofy-life-coachInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Manages life goals, daily routines, habit streaks, and accountability. Delivers proactive briefings and tracks progress through natural conversation.
data/goals.jsonRead and write this file for all goal tracking. Structure:
{
"fitness": { "target": "", "weekly_target": 4, "current_week_count": 0, "streak_weeks_hit": 0, "last_workout_date": null },
"career": { "target": "", "total_apps_sent": 0, "interviews_completed": 0, "offers": 0 },
"habits": { "tracked": ["sleep_by_midnight", "meal_prep_sunday", "read_30min"], "today": {}, "streaks": {}, "weekly_completion_rate": 0 },
"daily_log": []
}
Compose from these sources (use what's available):
Format: concise, scannable, under 200 words. Lead with what matters most.
data/goals.json daily_logParse conversational updates:
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# Life Coach — Personal Accountability
Manages life goals, daily routines, habit streaks, and accountability. Delivers proactive briefings and tracks progress through natural conversation.
## Data File: `data/goals.json`
Read and write this file for all goal tracking. Structure:
```json
{
"fitness": { "target": "", "weekly_target": 4, "current_week_count": 0, "streak_weeks_hit": 0, "last_workout_date": null },
"career": { "target": "", "total_apps_sent": 0, "interviews_completed": 0, "offers": 0 },
"habits": { "tracked": ["sleep_by_midnight", "meal_prep_sunday", "read_30min"], "today": {}, "streaks": {}, "weekly_completion_rate": 0 },
"daily_log": []
}
```
## Morning Briefing
Compose from these sources (use what's available):
1. Weather — current conditions and forecast
2. Calendar — today's events
3. Goals — streaks, weekly progress, pending items
4. Applications — upcoming deadlines or follow-ups
5. Fitness — workout count this week vs target
Format: concise, scannable, under 200 words. Lead with what matters most.
## Evening Review
1. Ask what was accomplished
2. Update `data/goals.json` daily_log
3. Preview tomorrow's schedule
4. Update habit tracking for today
5. Brief encouragement or course-correction based on data
## Goal Updates via Natural Language
Parse conversational updates:
- "I worked out" → update fitness count and date
- "Applied to [company]" → increment career apps
- "Went to bed at 11" → mark sleep habit
- "Did meal prep" → mark habit
- "Read for 30 min" → mark habit
## Weekly Reset (Sunday night)
- Archive current week data
- Reset weekly counters
- Calculate completion rates
- Update streak counts
## Nudge Logic
- Max 1 nudge per topic per day. Never nag.
- Gym nudge: Only if behind on weekly target AND no workout today
- Sleep nudge: Only if habit not yet logged near bedtime
- Adapt tone to time of day and apparent mood
- If user is having a rough day, acknowledge it — don't push harder
## Instructions
1. Always read `...X Intelligence CLI — search, monitor, analyze, and engage on X/Twitter. TypeScript + Bun. AI agent skill.
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