Personal Analytics

Know thyself. Work smarter. Discover patterns you didn't know existed.

Personal Analytics analyzes your conversation patterns to surface actionable insights about your work style, interests, and productivity—all while keeping your data completely private and local.

Features

• ⏰ Time Pattern Analysis - When you chat, for how long, productivity peaks
• 📚 Topic Tracking - What you discuss most, emerging interests
• 😊 Sentiment Monitoring - Mood trends, stress indicators
• 💡 Productivity Insights - Task completion, optimal work times
• 📊 Beautiful Reports - Weekly/monthly summaries
• 🔗 Proactive Research Integration - Auto-suggest monitoring topics
• 🔒 Privacy First - All local, no external data, opt-in design

Quick Start

# 1. Setup
cp config.example.json config.json

# 2. Enable tracking
python3 scripts/enable.py

# 3. Analyze (after some sessions)
python3 scripts/analyze.py --insights

# 4. Generate weekly report
python3 scripts/report.py weekly

# 5. Get topic recommendations
python3 scripts/recommend.py --explain

Privacy Guarantee

🔒 Your data never leaves your machine.

• Raw conversations NOT stored
• Only aggregated statistics saved
• All analysis happens locally
• No external APIs for analysis
• Data files are gitignored
• Delete anytime with one command

What Gets Tracked

✅ Tracked (Aggregated Only)

• Session timestamps and duration
• Topic frequencies
• Sentiment distribution
• Productivity markers
• Time-of-day patterns

❌ NOT Tracked

• Raw message content
• Personal information
• Sensitive data (passwords, keys)
• Specific conversation details

Use Cases

📈 Optimize Your Schedule

Discover when you're most productive and schedule deep work accordingly.

Example Insight:

"Your peak productivity is 09:00-11:00 on Wednesdays. Task completion is 68% faster during this window."

🎯 Focus on What Matters

Identify topics you're spending time on and decide if they align with your goals.

Example Insight:

"You've discussed 'Docker deployment' 23 times this month. Consider monitoring 'Docker security updates' proactively."

😊 Track Well-being

Monitor stress indicators, late-night work, and mood trends.

Example Insight:

"Stress keywords decreased 40% this week. Work-life balance improving! 🎉"

💡 Discover Hidden Interests

Surface emerging topics you didn't realize you cared about.

Example Insight:

"New interest detected: 'Rust' (12 mentions this week, 0 last week). Want to monitor Rust language updates?"

Commands

Enable/Disable

# Enable tracking
python3 scripts/enable.py

# Disable tracking
python3 scripts/disable.py

# Check status
python3 scripts/status.py

Analyze

# Analyze all data
python3 scripts/analyze.py

# Analyze date range
python3 scripts/analyze.py --since "2026-01-01" --until "2026-01-31"

# With insights
python3 scripts/analyze.py --insights

# JSON output
python3 scripts/analyze.py --json

Reports

# Weekly report
python3 scripts/report.py weekly

# Monthly report
python3 scripts/report.py monthly

# Custom range
python3 scripts/report.py custom --since "2026-01-01" --until "2026-01-31"

# Save to file
python3 scripts/report.py weekly --output report.md

# Send via Telegram
python3 scripts/report.py weekly --send

Recommendations

# Get topic recommendations
python3 scripts/recommend.py

# With explanations
python3 scripts/recommend.py --explain

# Set threshold (min mentions)
python3 scripts/recommend.py --threshold 5

# Auto-add to proactive-research
python3 scripts/recommend.py --auto-add

Sample Report

# 📊 Weekly Analytics Report
**Jan 22 - Jan 28, 2026**

## 🎯 Highlights

- **Most productive day:** Wednesday (6 tasks completed)
- **Peak hours:** 09:00-11:00
- **Emerging topic:** Rust (+1200%)
- **Mood trend:** ↗️ 78% positive (up from 65%)

## ⏰ Time Patterns

Mon  ████░░░░░░░░  4h
Tue  ██████░░░░░░  6h 30m
Wed  ████████░░░░  8h 15m  ← Peak
Thu  ██████░░░░░░  5h
Fri  ████░░░░░░░░  3h 45m

## 📚 Top Topics

1. **Python** (32 sessions)
2. **FM26** (28 sessions)
3. **Audio Engineering** (15 sessions)

## 💡 Recommendations

- Schedule deep work 09:00-11:00 (your peak)
- Monitor "Rust updates" (new interest)
- Avoid late-night sessions (22% slower)

Integration

Proactive Research

Personal Analytics automatically suggests topics for monitoring:

python3 scripts/recommend.py --auto-add

Flow:

1. Analyze conversation patterns
2. Identify frequently discussed topics
3. Suggest adding to proactive-research
4. One-click setup

Moltbot Session Hooks

For automated tracking, integrate with Moltbot:

# On session end
python3 /path/to/personal-analytics/scripts/session_tracker.py \
  message \
  --session-id <id> \
  --topics "Python,Docker" \
  --sentiment positive

Configuration

See SKILL.md for complete configuration options.

Key Settings

{
  "enabled": true,
  "privacy": {
    "auto_delete_after_days": 90,
    "exclude_patterns": ["password", "secret"]
  },
  "insights": {
    "productivity_markers": ["completed", "shipped", "fixed"],
    "stress_indicators": ["urgent", "critical", "broken"]
  }
}

Data Storage

.analytics_data.json

Aggregated statistics only (privacy-safe):

{
  "sessions": [{
    "id": "uuid",
    "start": "2026-01-28T10:00:00Z",
    "duration_seconds": 900,
    "topics": ["Python", "Docker"],
    "sentiment": "positive",
    "productivity_score": 0.8
  }],
  "topic_stats": {
    "Python": {
      "total_mentions": 145,
      "trend": "stable"
    }
  }
}

Requirements

• Python 3.8+
• Optional: proactive-research skill (for recommendations)

FAQ

Q: Is my data shared?

No. Everything stays on your machine. No external APIs for analysis.

Q: Can I see the raw data?

Yes. Check .analytics_data.json - only aggregated stats, no message content.

Q: How do I delete everything?

rm .analytics_data.json .topic_cache.json

Q: Does this slow down my assistant?

No. Analysis runs separately, doesn't affect chat performance.

License

MIT

Credits

Built for ClawdHub by the Moltmates team. Privacy-first design inspired by Quantified Self movement.