Complete Activity Tracking System - Final Status

Installation Date: 2025-11-17 System Status: ✅ FULLY OPERATIONAL - ALL TRACKERS ACTIVE

🎉 What You Now Have

A complete activity tracking ecosystem that monitors EVERYTHING:

Every website you visit
Every line of code you write
Every Claude tool you use
Every directory you work in
Every git commit you make
Every Chrome profile you use
Every Google account you’re in
Every application you interact with

Total Trackers: 8 active watchers + 1 browser extension = 9 tracking systems

📊 Active Trackers (8/8 - 100%)

Custom Watchers (5)

✅ Terminal watcher          (PID: 9358) - Every 10s
✅ Git watcher              (PID: 9360) - Every 30s
✅ Chrome profile watcher   (PID: 9362) - Every 30s
✅ Claude activity watcher  (PID: 9364) - Every 15s
✅ Claude tool usage       (PID: 9366) - Every 10s

Built-in Watchers (3)

✅ Window tracking  - Active app & titles
✅ AFK detection    - Active vs idle time
✅ Browser extension - Web browsing (Chrome)

🗂️ Data Buckets (9 Buckets Active)

Bucket	What It Tracks	Events
`aw-watcher-terminal_*`	🖥️ Terminal & directories	Active
`aw-watcher-git_*`	🔀 Git repos & commits	Active
`aw-watcher-chrome-profiles_*`	👤 Chrome profiles & Google accounts	Active
`aw-watcher-claude_*`	🤖 Claude sessions	Active
`aw-watcher-claude-tools_*`	🔧 Claude tool usage	Active
`aw-watcher-window_*`	🪟 Active applications	Active
`aw-watcher-afk_*`	⏰ Active/idle time	Active
`aw-watcher-web-chrome`	🌐 Websites visited	Active

🎯 What Each Tracker Monitors

1. 🤖 Claude Activity Tracker NEW!

What: AI-assisted development sessions Tracks:

Active Claude sessions
Session duration
Files modified during session
Project context
Working directory

Use for:

Tracking AI-assisted dev time
Understanding Claude usage patterns
Project-level AI assistance metrics

2. 🔧 Claude Tool Usage Tracker NEW!

What: Specific Claude tool usage (Read, Write, Edit, Bash) Tracks:

Individual tool calls
File types being worked on
Tool frequency
Recent files accessed

Use for:

Understanding which tools you use most
Analyzing development patterns
Productivity metrics

3. 🖥️ Terminal Activity Tracker

What: Terminal and command-line work Tracks:

Working directories
Shell type (zsh, bash)
Terminal app (iTerm, Terminal)
Git repository detection

Use for:

Time per project directory
Most active directories
Terminal session patterns

4. 🔀 Git & GitHub Tracker

What: Version control activity Tracks:

Repository name and path
Current branch
GitHub owner/repo
Modified files count
Commit status
Ahead/behind remote

Use for:

Time per repository
Branch switching patterns
GitHub project tracking

5. 👤 Chrome Profile & Google Account Tracker

What: Browser profiles and identities Tracks:

Active Chrome profile
Google account emails
Profile display names
Account switching

Use for:

Work vs personal account usage
Multi-account management
Profile switching frequency

6. 🌐 Browser Activity Tracker

What: Web browsing (via browser extension) Tracks:

Specific URLs visited
Page titles
Time per website
Domain-level analytics

Use for:

Time per website
Productivity analysis
Research tracking

7. 🪟 Window Tracker

What: Active applications (built-in) Tracks:

Active application
Window titles
App switching

Use for:

Application time tracking
Context switching analysis
Overall productivity

8. ⏰ AFK Tracker

What: Active vs idle time (built-in) Tracks:

Keyboard/mouse activity
Active vs idle time
AFK detection

Use for:

Actual working time
Break patterns
Productivity metrics

🚀 Quick Start

Check System Status

# View all watchers
./scripts/start-custom-watchers.sh status

# View all buckets
curl -s http://localhost:5600/api/0/buckets/ | jq 'keys'

Control Watchers

# Start all watchers
./scripts/start-custom-watchers.sh all

# Start only Claude watchers
./scripts/start-custom-watchers.sh claude

# Stop all watchers
./scripts/start-custom-watchers.sh stop

# Restart all
./scripts/start-custom-watchers.sh restart

View Logs

# Claude activity
tail -f ~/Library/Application\ Support/activitywatch/logs/aw-watcher-claude.log

# Claude tool usage
tail -f ~/Library/Application\ Support/activitywatch/logs/aw-watcher-claude-tools.log

# Terminal
tail -f ~/Library/Application\ Support/activitywatch/logs/aw-watcher-terminal.log

# Git
tail -f ~/Library/Application\ Support/activitywatch/logs/aw-watcher-git.log

# Chrome profiles
tail -f ~/Library/Application\ Support/activitywatch/logs/aw-watcher-chrome-profiles.log

View Data

# Open web dashboard
open http://localhost:5600

# Check browser stats
venv/bin/python3 scripts/show-browser-stats.py

# Verify browser extension
./scripts/verify-browser-extension.sh

📈 Example Queries

Total AI-Assisted Development Time Today

from aw_client import ActivityWatchClient
from datetime import datetime

client = ActivityWatchClient()
today = datetime.now().replace(hour=0, minute=0, second=0)

bucket_id = f"aw-watcher-claude_{client.client_hostname}"
events = client.get_events(bucket_id, start=today)

total_time = sum(e["duration"].total_seconds() if hasattr(e["duration"], 'total_seconds') else e["duration"] for e in events)
print(f"Claude usage today: {total_time/3600:.2f} hours")

Most Used Claude Tools Today

from collections import defaultdict

bucket_id = f"aw-watcher-claude-tools_{client.client_hostname}"
events = client.get_events(bucket_id, start=today)

tools = defaultdict(int)
for e in events:
    for tool, count in e["data"].get("tools_used", {}).items():
        tools[tool] += count

print("Tool usage today:")
for tool, count in sorted(tools.items(), key=lambda x: x[1], reverse=True):
    print(f"  {tool}: {count} times")

Complete Development Summary

from aw_client import ActivityWatchClient
from datetime import datetime

client = ActivityWatchClient()
today = datetime.now().replace(hour=0, minute=0, second=0)

# Get all development-related buckets
claude_bucket = f"aw-watcher-claude_{client.client_hostname}"
terminal_bucket = f"aw-watcher-terminal_{client.client_hostname}"
git_bucket = f"aw-watcher-git_{client.client_hostname}"

claude_events = client.get_events(claude_bucket, start=today)
terminal_events = client.get_events(terminal_bucket, start=today)
git_events = client.get_events(git_bucket, start=today)

claude_time = sum(e["duration"].total_seconds() if hasattr(e["duration"], 'total_seconds') else e["duration"] for e in claude_events)
terminal_time = sum(e["duration"].total_seconds() if hasattr(e["duration"], 'total_seconds') else e["duration"] for e in terminal_events)
git_time = sum(e["duration"].total_seconds() if hasattr(e["duration"], 'total_seconds') else e["duration"] for e in git_events)

print("📊 Development Summary Today:")
print(f"  Claude-assisted: {claude_time/3600:.2f}h")
print(f"  Terminal work: {terminal_time/3600:.2f}h")
print(f"  Git activity: {git_time/3600:.2f}h")
print(f"  AI-assisted ratio: {claude_time/(claude_time+terminal_time)*100:.1f}%")

📚 Documentation Map

Quick References

Tracking Guides

Technical Documentation

| Document | Purpose | |———-|———| | scripts/README-CUSTOM-WATCHERS.md | Watcher development | | .claude/skills/activitywatch-integration/ | Complete API reference |

🎨 Real-World Use Cases

1. AI-Assisted Productivity Analysis

Track how Claude impacts your development speed:

# Calculate files modified per hour with vs without Claude
claude_hours = claude_time / 3600
files_with_claude = sum(e["data"].get("files_modified", 0) for e in claude_events)
files_per_hour = files_with_claude / max(claude_hours, 0.1)

print(f"Productivity with Claude: {files_per_hour:.1f} files/hour")

2. Multi-Account Work Tracking

See which Google account you use for which projects:

# Correlate Chrome profiles with git repos
profile_events = client.get_events(f"aw-watcher-chrome-profiles_{client.client_hostname}", start=today)

# Group by account and time
by_account = {}
for e in profile_events:
    accounts = e["data"].get("google_accounts", [])
    for acc in accounts:
        email = acc.get("email")
        if email:
            duration = e["duration"].total_seconds() if hasattr(e["duration"], 'total_seconds') else e["duration"]
            by_account[email] = by_account.get(email, 0) + duration

print("Account usage:")
for email, duration in sorted(by_account.items(), key=lambda x: x[1], reverse=True):
    print(f"  {email}: {duration/3600:.2f}h")

3. Project Time Allocation

See where your development time goes:

# Time per project (from terminal + git data)
from collections import defaultdict

by_project = defaultdict(float)

for e in terminal_events:
    cwd = e["data"].get("cwd", "")
    project = cwd.split("/")[-1] if cwd else "Unknown"
    duration = e["duration"].total_seconds() if hasattr(e["duration"], 'total_seconds') else e["duration"]
    by_project[project] += duration

for e in git_events:
    project = e["data"].get("repo_name", "Unknown")
    duration = e["duration"].total_seconds() if hasattr(e["duration"], 'total_seconds') else e["duration"]
    by_project[project] += duration

print("Time by project:")
for project, duration in sorted(by_project.items(), key=lambda x: x[1], reverse=True)[:10]:
    print(f"  {project}: {duration/3600:.2f}h")

4. Tool Usage Patterns

Understand your development workflow:

# Analyze tool usage across all Claude sessions
bucket_id = f"aw-watcher-claude-tools_{client.client_hostname}"
week_ago = datetime.now() - timedelta(days=7)
events = client.get_events(bucket_id, start=week_ago)

tools = defaultdict(int)
for e in events:
    for tool, count in e["data"].get("tools_used", {}).items():
        tools[tool] += count

print("Tool usage (last 7 days):")
for tool, count in sorted(tools.items(), key=lambda x: x[1], reverse=True):
    print(f"  {tool}: {count} times")

🔄 Auto-Start Configuration

To have all watchers start automatically on login:

# LaunchAgent plist file (already created if you followed previous guides)
cat > ~/Library/LaunchAgents/com.activitywatch.custom-watchers.plist << 'EOF'
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
    <key>Label</key>
    <string>com.activitywatch.custom-watchers</string>
    <key>ProgramArguments</key>
    <array>
        <string>/Users/alyshialedlie/activitywatch/scripts/start-custom-watchers.sh</string>
        <string>all</string>
    </array>
    <key>RunAtLoad</key>
    <true/>
    <key>StandardOutPath</key>
    <string>/Users/alyshialedlie/Library/Application Support/activitywatch/logs/custom-watchers.log</string>
    <key>StandardErrorPath</key>
    <string>/Users/alyshialedlie/Library/Application Support/activitywatch/logs/custom-watchers-error.log</string>
</dict>
</plist>
EOF

# Load the agent
launchctl load ~/Library/LaunchAgents/com.activitywatch.custom-watchers.plist

📊 System Health Check

Run this comprehensive check:

#!/bin/bash
echo "🔍 ActivityWatch Complete System Health Check"
echo "=============================================="
echo ""

# Server
echo -n "ActivityWatch Server: "
curl -s http://localhost:5600/api/0/info > /dev/null && echo "✅ Running" || echo "❌ Not running"

# Custom Watchers
echo ""
echo "Custom Watchers:"
./scripts/start-custom-watchers.sh status

# Buckets
echo ""
echo "Data Buckets:"
echo "=============================================="
curl -s http://localhost:5600/api/0/buckets/ | jq -r 'keys[]' | while read bucket; do
    count=$(curl -s "http://localhost:5600/api/0/buckets/$bucket/events" | jq 'length' 2>/dev/null || echo "0")

    case $bucket in
        *claude-tools*) echo "   🔧 $bucket: $count events" ;;
        *claude*) echo "   🤖 $bucket: $count events" ;;
        *web*) echo "   🌐 $bucket: $count events" ;;
        *chrome-profiles*) echo "   👤 $bucket: $count events" ;;
        *terminal*) echo "   🖥️  $bucket: $count events" ;;
        *git*) echo "   🔀 $bucket: $count events" ;;
        *window*) echo "   🪟 $bucket: $count events" ;;
        *afk*) echo "   ⏰ $bucket: $count events" ;;
        *) echo "   📊 $bucket: $count events" ;;
    esac
done

echo ""
echo "=============================================="
echo "✅ System health check complete!"

🎯 What You Can Now Track

✅ Development Work

AI-assisted coding time
Tool usage patterns
Files created/modified
Projects worked on

✅ Version Control

Repositories active
Branches worked on
Commit patterns
GitHub projects

✅ Web Activity

Websites visited
Research time
Documentation reading
Social media usage

✅ Account Management

Google account switching
Work vs personal time
Chrome profile usage
Multi-account patterns

✅ Overall Productivity

Active vs idle time
Application usage
Context switching
Daily patterns

🎉 Final Status

System: ✅ Fully Operational Trackers: 8/8 Active (100%) Data Collection: Active Documentation: Complete

Installation Journey Complete!

You now have a world-class activity tracking system that monitors your entire digital workflow - from AI-assisted coding to web browsing to multi-account management.

Dashboard: http://localhost:5600 Support: See .claude/skills/activitywatch-integration/

Created: 2025-11-17 ActivityWatch Version: v0.13.2 Custom Trackers: 5 Total Tracking Systems: 9 Status: 🎉 COMPLETE

Tags: activitywatch, automation, tracking

Categories: productivity, work-updates

Updated: November 17, 2025