personal-analytics

# 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. ## Core Capabilities 1. **Session Analysis** - When you chat, for how long, productivity patterns 2. **Topic Tracking** - What subjects come up repeatedly, trending interests 3. **Sentiment Patterns** - Mood tracking over time, stress indicators 4. **Productivity Insights** - When you're most effective, optimal work times 5. **Weekly/Monthly Reports** - Beautiful summaries of your patterns 6. **Topic Recommendations** - Auto-suggest topics for proactive-research monitoring ## Privacy First 🔒 **All analysis happens locally. Nothing leaves your machine.** - Raw conversations **never** stored - Only aggregated statistics saved - Opt-in design (must enable) - Data deletion anytime - No external APIs for analysis - Gitignored data files ## Quick Start ```bash # Initialize cp config.example.json config.json # Enable tracking python3 scripts/enable.py # Analyze current sessions python3 scripts/analyze.py # Generate report python3 scripts/report.py weekly # Get topic recommendations python3 scripts/recommend.py ``` ## What Gets Tracked ### Session Metadata - Timestamp (start/end) - Duration - Message count - Primary topics discussed - Sentiment (positive/neutral/negative/mixed) - Productivity markers (tasks completed, decisions made) ### Aggregated Stats - Hourly activity heatmap - Topic frequency over time - Average session duration - Productivity by time of day - Sentiment trends ### What's NOT Tracked - ❌ Raw message content - ❌ Personal information - ❌ Sensitive data (passwords, keys, etc.) - ❌ Specific conversations ## Configuration ### config.json ```json { "enabled": true, "tracking": { "sessions": true, "topics": true, "sentiment": true, "productivity": true }, "privacy": { "min_aggregation_window_hours": 24, "auto_delete_after_days": 90, "exclude_patterns": ["password", "secret", "token", "key"] }, "insights": { "productivity_markers": [ "completed", "shipped", "fixed", "merged", "deployed" ], "stress_indicators": [ "urgent", "asap", "critical", "broken", "emergency" ] }, "reports": { "weekly_day": "sunday", "weekly_time": "20:00", "auto_send": false }, "integrations": { "proactive_research": { "auto_suggest_topics": true, "suggestion_threshold": 3 } } } ``` ## Scripts ### analyze.py Analyze conversation patterns: ```bash # Analyze all available data python3 scripts/analyze.py # Analyze specific time range python3 scripts/analyze.py --since "2026-01-01" --until "2026-01-31" # Analyze and show insights python3 scripts/analyze.py --insights # Verbose output python3 scripts/analyze.py --verbose ``` **Output:** ``` 📊 Personal Analytics Analysis Period: Jan 1 - Jan 28, 2026 (28 days) Session Summary: Total sessions: 145 Total time: 18h 32m Avg session: 7m 40s Most active: Tuesday 10:00-11:00 Topics (Top 10): 1. Python (32 sessions) 2. FM26 (28 sessions) 3. Dirac Live (15 sessions) 4. ETH/crypto (12 sessions) 5. Docker (11 sessions) ... Productivity: High productivity: 09:00-12:00, 14:00-16:00 Low productivity: Late night (after 22:00) Peak day: Wednesday Sentiment: Positive: 62% Neutral: 28% Negative: 8% Mixed: 2% ``` ### report.py Generate beautiful reports: ```bash # 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" # Export to file python3 scripts/report.py weekly --output report.md # Send via Telegram python3 scripts/report.py weekly --send ``` **Report Format:** ```markdown # 📊 Weekly Analytics Report **Jan 22 - Jan 28, 2026** ## 🎯 Highlights - **Most productive day:** Wednesday (4 tasks completed) - **Peak hours:** 09:00-11:00 (3h 45m focused work) - **Emerging topic:** Rust (mentioned 12 times, +200% from last week) - **Mood trend:** ↗️ Improving (78% positive, up from 65%) ## ⏰ Time Patterns ### Activity Heatmap ``` Mon ████░░░░░░░░░░░░░░░░░░░░ 4h Tue ██████████░░░░░░░░░░░░░░ 6h 30m Wed ████████████░░░░░░░░░░░░ 8h 15m ← Peak Thu ██████░░░░░░░░░░░░░░░░░░ 5h Fri ████░░░░░░░░░░░░░░░░░░░░ 3h 45m Sat ██░░░░░░░░░░░░░░░░░░░░░░ 1h 30m Sun ░░░░░░░░░░░░░░░░░░░░░░░░ 45m ``` ### Hourly Distribution ``` 06-09: ██░░░░░░░░ (12%) 09-12: ████████░░ (38%) ← Peak productivity 12-14: ███░░░░░░░ (15%) 14-17: █████░░░░░ (24%) 17-22: ██░░░░░░░░ (11%) ``` ## 📚 Topic Insights ### Top Topics This Week 1. **Python Development** (32 sessions) - Focus: FastAPI, async, testing - Trend: Steady - Suggestion: Monitor "Python 3.13 features" 2. **FM26** (28 sessions) - Focus: Tactics, transfers, editor - Trend: ↗️ +15% - Suggestion: Already monitoring "FM26 patches" ✓ 3. **Audio Engineering** (15 sessions) - Focus: Dirac Live, room correction, bass management - Trend: 🆕 New topic - Suggestion: Monitor "Dirac Live updates" ### Emerging Topics - **Rust** (12 mentions, first appearance) - **Kubernetes** (8 mentions, +300%) - **Machine Learning** (6 mentions) ## 💡 Productivity Insights ### Task Completion - Total tasks: 23 completed - Success rate: 87% - Best day: Wednesday (6 tasks) - Best time: Morning (09:00-12:00) ### Focus Sessions - Long sessions (>30m): 8 - Average focus time: 18m - Longest session: 1h 42m (Wed 10:15) ### Problem-Solving Speed - Quick wins (<15m): 14 problems - Complex issues (>1h): 3 problems - Average: 24m per problem ## 😊 Sentiment & Well-being ### Overall Mood ``` 😊 Positive ████████████████░░ 78% (↗️ +13%) 😐 Neutral ████░░░░░░░░░░░░░░ 18% 😟 Negative ██░░░░░░░░░░░░░░░░ 4% ``` ### Stress Indicators - High stress: 3 sessions (down from 7) - Urgent keywords: 5 (down from 12) - Late-night work: 2 sessions (down from 8) **Insight:** Stress levels decreasing. Good work-life balance this week! 🎉 ## 🎯 Recommendations ### For Proactive Research Based on your interests this week, consider monitoring: 1. **Rust language updates** (mentioned 12x, new interest) 2. **Dirac Live releases** (mentioned 15x, active problem-solving) 3. **Kubernetes security** (mentioned 8x, DevOps focus) ### Productivity Tips - **Schedule deep work 09:00-11:00** (your peak productivity) - **Batch meetings after lunch** (14:00-16:00 is secondary peak) - **Avoid late-night sessions** (22% slower problem-solving) ### Topics to Explore Based on your current interests, you might enjoy: - Async Rust patterns (combines Rust + async focus) - Kubernetes observability (combines K8s + monitoring) - Audio DSP with Python (combines audio + Python) --- _Generated by Personal Analytics • Privacy-first, locally processed_ ``` ### recommend.py Get topic recommendations for proactive-research: ```bash # Get recommendations python3 scripts/recommend.py # Show reasoning python3 scripts/recommend.py --explain # Auto-add to proactive-research python3 scripts/recommend.py --auto-add # Set threshold (minimum mentions) python3 scripts/recommend.py --threshold 5 ``` **Output:** ``` 💡 Topic Recommendations for Proactive Research Based on your conversation patterns: 1. Rust Language Updates Mentioned: 12 times this week (new topic) Reason: Emerging interest, high engagement Suggested query: "Rust language updates releases" Suggested frequency: weekly 2. Dirac Live Updates Mentioned: 15 times this week Reason: Active problem-solving, technical depth Suggested query: "Dirac Live update release" Suggested frequency: daily 3. FM26 Patches Mentioned: 28 times this week Reason: Consistent interest over time NOTE: Already monitoring! ✓ Would you like to add these topics to proactive-research? [y/N] ``` ### session_tracker.py Track individual sessions (called by Moltbot): ```bash # Log session start python3 scripts/session_tracker.py start --channel telegram # Log session end python3 scripts/session_tracker.py end --session-id <id> # Log message (topics, sentiment) python3 scripts/session_tracker.py message --session-id <id> \ --topics "Python,Docker" \ --sentiment positive ``` This script is designed to be called by Moltbot hooks, not manually. ### enable.py / disable.py Manage tracking: ```bash # Enable tracking python3 scripts/enable.py # Disable tracking python3 scripts/disable.py # Show status python3 scripts/status.py ``` ## Integration with Moltbot Personal Analytics can integrate with Moltbot session lifecycle: ### Hook Points 1. **Session Start** - Log timestamp, channel 2. **Session End** - Calculate duration, save stats 3. **Message Received** - Extract topics (lightweight), detect sentiment ### Recommended Setup Add to Moltbot SOUL.md: ```markdown ## Personal Analytics Integration After each session ends, if personal-analytics is enabled: 1. Extract primary topics discussed (max 5) 2. Determine overall sentiment 3. Detect productivity markers (tasks completed) 4. Log to personal-analytics via session_tracker.py ``` ## Data Storage ### .analytics_data.json Aggregated statistics only: ```json { "sessions": [ { "id": "session_uuid", "start": "2026-01-28T10:00:00Z", "end": "2026-01-28T10:15:00Z", "duration_seconds": 900, "channel": "telegram", "topics": ["Python", "Docker"], "sentiment": "positive", "productivity_score": 0.8, "tasks_completed": 1 } ], "topic_stats": { "Python": { "total_mentions": 145, "last_seen": "2026-01-28T10:15:00Z", "trend": "stable" } }, "time_stats": { "hourly_distribution": { "09": 23, "10": 45, "11": 38, ... }, "daily_distribution": { "monday": 120, "tuesday": 98, ... } }, "sentiment_stats": { "positive": 145, "neutral": 62, "negative": 18, "mixed": 5 } } ``` ### .topic_cache.json Topic extraction cache (temporary): ```json { "hash_12345": ["Python", "FastAPI", "testing"], "hash_67890": ["FM26", "tactics"] } ``` Auto-deleted after 7 days. ## Insights & Patterns ### Time-Based Insights **Productivity by Hour:** - Analyzes task completion rate by hour - Identifies peak productivity windows - Suggests optimal work scheduling **Day of Week Patterns:** - Activity levels per day - Best days for deep work - Meeting-heavy vs focus-heavy days ### Topic Insights **Topic Clustering:** - Groups related topics - Identifies emerging interests - Detects topic trends (rising, falling, stable) **Depth Analysis:** - Surface-level mentions vs deep dives - Problem-solving topics vs casual chat - Technical vs non-technical ratio ### Sentiment Insights **Mood Tracking:** - Overall sentiment trends - Correlation with time of day - Stress indicator detection **Well-being Metrics:** - Late-night work frequency - Urgent/stress keywords - Work-life balance indicators ## Privacy Controls ### Exclusion Patterns Automatically exclude sensitive data: ```json { "privacy": { "exclude_patterns": [ "password", "token", "key", "secret", "credit card", "ssn", "api key" ] } } ``` ### Data Retention Auto-delete old data: ```json { "privacy": { "auto_delete_after_days": 90, "keep_aggregated_stats": true } } ``` ### Manual Deletion ```bash # Delete all data python3 scripts/delete_data.py --all # Delete specific date range python3 scripts/delete_data.py --since "2026-01-01" --until "2026-01-31"