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# RTK Token Savings Audit Guide
Complete guide to analyzing your rtk token savings with temporal breakdowns and data exports.
## Overview
The `rtk gain` command provides comprehensive analytics for tracking your token savings across time periods.
**Database Location**: `~/.local/share/rtk/history.db`
**Retention Policy**: 90 days
**Scope**: Global across all projects, worktrees, and Claude sessions
## Quick Reference
```bash
# Default summary view
rtk gain
# Temporal breakdowns
rtk gain --daily # All days since tracking started
rtk gain --weekly # Aggregated by week
rtk gain --monthly # Aggregated by month
rtk gain --all # Show all breakdowns at once
# Export formats
rtk gain --all --format json > savings.json
rtk gain --all --format csv > savings.csv
# Combined flags
rtk gain --graph --history --quota # Classic view with extras
rtk gain --daily --weekly --monthly # Multiple breakdowns
# Reset all tracking data
rtk gain --reset # prompts [y/N] before deleting
rtk gain --reset --yes # skip prompt (CI/scripts)
```
## Command Options
### Temporal Flags
| Flag | Description | Output |
|------|-------------|--------|
| `--daily` | Day-by-day breakdown | All days with full metrics |
| `--weekly` | Week-by-week breakdown | Aggregated by Sunday-Saturday weeks |
| `--monthly` | Month-by-month breakdown | Aggregated by calendar month |
| `--all` | All time breakdowns | Daily + Weekly + Monthly combined |
### Classic Flags (still available)
| Flag | Description |
|------|-------------|
| `--graph` | ASCII graph of last 30 days |
| `--history` | Recent 10 commands |
| `--quota` | Monthly quota analysis (Pro/5x/20x tiers) |
| `--tier <TIER>` | Quota tier: pro, 5x, 20x (default: 20x) |
### Reset Flag
| Flag | Description |
|------|-------------|
| `--reset` | Permanently delete all tracking data (commands + parse failures) |
| `--yes` | Skip the confirmation prompt (for CI/scripts) |
> **Warning**: `--reset` is irreversible. It clears both the `commands` and `parse_failures` tables atomically. A `[y/N]` confirmation prompt is shown by default. In non-interactive environments (piped stdin), it defaults to `N` unless `--yes` is passed.
### Export Formats
| Format | Flag | Use Case |
|--------|------|----------|
| `text` | `--format text` (default) | Terminal display |
| `json` | `--format json` | Programmatic analysis, APIs |
| `csv` | `--format csv` | Excel, data analysis, plotting |
## Output Examples
### Daily Breakdown
```
📅 Daily Breakdown (3 days)
════════════════════════════════════════════════════════════════
Date Cmds Input Output Saved Save%
────────────────────────────────────────────────────────────────
2026-01-28 89 380.9K 26.7K 355.8K 93.4%
2026-01-29 102 894.5K 32.4K 863.7K 96.6%
2026-01-30 5 749 55 694 92.7%
────────────────────────────────────────────────────────────────
TOTAL 196 1.3M 59.2K 1.2M 95.6%
```
**Metrics explained:**
- **Cmds**: Number of rtk commands executed
- **Input**: Estimated tokens from raw command output
- **Output**: Actual tokens after rtk filtering
- **Saved**: Input - Output (tokens prevented from reaching LLM)
- **Save%**: Percentage reduction (Saved / Input × 100)
### Weekly Breakdown
```
📊 Weekly Breakdown (1 weeks)
════════════════════════════════════════════════════════════════════════
Week Cmds Input Output Saved Save%
────────────────────────────────────────────────────────────────────────
01-26 → 02-01 196 1.3M 59.2K 1.2M 95.6%
────────────────────────────────────────────────────────────────────────
TOTAL 196 1.3M 59.2K 1.2M 95.6%
```
**Week definition**: Sunday to Saturday (ISO week starting Sunday at 00:00)
### Monthly Breakdown
```
📆 Monthly Breakdown (1 months)
════════════════════════════════════════════════════════════════
Month Cmds Input Output Saved Save%
────────────────────────────────────────────────────────────────
2026-01 196 1.3M 59.2K 1.2M 95.6%
────────────────────────────────────────────────────────────────
TOTAL 196 1.3M 59.2K 1.2M 95.6%
```
**Month format**: YYYY-MM (calendar month)
### JSON Export
```json
{
"summary": {
"total_commands": 196,
"total_input": 1276098,
"total_output": 59244,
"total_saved": 1220217,
"avg_savings_pct": 95.62
},
"daily": [
{
"date": "2026-01-28",
"commands": 89,
"input_tokens": 380894,
"output_tokens": 26744,
"saved_tokens": 355779,
"savings_pct": 93.41
}
],
"weekly": [...],
"monthly": [...]
}
```
**Use cases:**
- API integration
- Custom dashboards
- Automated reporting
- Data pipeline ingestion
### CSV Export
```csv
# Daily Data
date,commands,input_tokens,output_tokens,saved_tokens,savings_pct
2026-01-28,89,380894,26744,355779,93.41
2026-01-29,102,894455,32445,863744,96.57
# Weekly Data
week_start,week_end,commands,input_tokens,output_tokens,saved_tokens,savings_pct
2026-01-26,2026-02-01,196,1276098,59244,1220217,95.62
# Monthly Data
month,commands,input_tokens,output_tokens,saved_tokens,savings_pct
2026-01,196,1276098,59244,1220217,95.62
```
**Use cases:**
- Excel analysis
- Python/R data science
- Google Sheets dashboards
- Matplotlib/seaborn plotting
## Analysis Workflows
### Weekly Progress Tracking
```bash
# Generate weekly report every Monday
rtk gain --weekly --format csv > reports/week-$(date +%Y-%W).csv
# Compare this week vs last week
rtk gain --weekly | tail -3
```
### Monthly Cost Analysis
```bash
# Export monthly data for budget review
rtk gain --monthly --format json | jq '.monthly[] |
{month, saved_tokens, quota_pct: (.saved_tokens / 6000000 * 100)}'
```
### Data Science Analysis
```python
import pandas as pd
import subprocess
# Get CSV data
result = subprocess.run(['rtk', 'gain', '--all', '--format', 'csv'],
capture_output=True, text=True)
# Parse daily data
lines = result.stdout.split('\n')
daily_start = lines.index('# Daily Data') + 2
daily_end = lines.index('', daily_start)
daily_df = pd.read_csv(pd.StringIO('\n'.join(lines[daily_start:daily_end])))
# Plot savings trend
daily_df['date'] = pd.to_datetime(daily_df['date'])
daily_df.plot(x='date', y='savings_pct', kind='line')
```
### Excel Analysis
1. Export CSV: `rtk gain --all --format csv > rtk-data.csv`
2. Open in Excel
3. Create pivot tables:
- Daily trends (line chart)
- Weekly totals (bar chart)
- Savings % distribution (histogram)
### Dashboard Creation
```bash
# Generate dashboard data daily via cron
0 0 * * * rtk gain --all --format json > /var/www/dashboard/rtk-stats.json
# Serve with static site
cat > index.html <<'EOF'
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
<canvas id="savings"></canvas>
<script>
fetch('rtk-stats.json')
.then(r => r.json())
.then(data => {
new Chart(document.getElementById('savings'), {
type: 'line',
data: {
labels: data.daily.map(d => d.date),
datasets: [{
label: 'Daily Savings %',
data: data.daily.map(d => d.savings_pct)
}]
}
});
});
</script>
EOF
```
## Understanding Token Savings
### Token Estimation
rtk estimates tokens using `text.len() / 4` (4 characters per token average).
**Accuracy**: ±10% compared to actual LLM tokenization (sufficient for trends).
### Savings Calculation
```
Input Tokens = estimate_tokens(raw_command_output)
Output Tokens = estimate_tokens(rtk_filtered_output)
Saved Tokens = Input - Output
Savings % = (Saved / Input) × 100
```
### Typical Savings by Command
| Command | Typical Savings | Mechanism |
|---------|----------------|-----------|
| `rtk git status` | 77-93% | Compact stat format |
| `rtk eslint` | 84% | Group by rule |
| `rtk jest` | 94-99% | Show failures only |
| `rtk vitest` | 94-99% | Show failures only |
| `rtk find` | 75% | Tree format |
| `rtk pnpm list` | 70-90% | Compact dependencies |
| `rtk grep` | 70% | Truncate + group |
## Database Management
### Inspect Raw Data
```bash
# Location
ls -lh ~/.local/share/rtk/history.db
# Schema
sqlite3 ~/.local/share/rtk/history.db ".schema"
# Recent records
sqlite3 ~/.local/share/rtk/history.db \
"SELECT timestamp, rtk_cmd, saved_tokens FROM commands
ORDER BY timestamp DESC LIMIT 10"
# Total database size
sqlite3 ~/.local/share/rtk/history.db \
"SELECT COUNT(*),
SUM(saved_tokens) as total_saved,
MIN(DATE(timestamp)) as first_record,
MAX(DATE(timestamp)) as last_record
FROM commands"
```
### Backup & Restore
```bash
# Backup
cp ~/.local/share/rtk/history.db ~/backups/rtk-history-$(date +%Y%m%d).db
# Restore
cp ~/backups/rtk-history-20260128.db ~/.local/share/rtk/history.db
# Export for migration
sqlite3 ~/.local/share/rtk/history.db .dump > rtk-backup.sql
```
### Cleanup
```bash
# Manual cleanup (older than 90 days)
sqlite3 ~/.local/share/rtk/history.db \
"DELETE FROM commands WHERE timestamp < datetime('now', '-90 days')"
# Reset all data
rm ~/.local/share/rtk/history.db
# Next rtk command will recreate database
```
## Integration Examples
### GitHub Actions CI/CD
```yaml
# .github/workflows/rtk-stats.yml
name: RTK Stats Report
on:
schedule:
- cron: '0 0 * * 1' # Weekly on Monday
jobs:
stats:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Install rtk
run: cargo install --path .
- name: Generate report
run: |
rtk gain --weekly --format json > stats/week-$(date +%Y-%W).json
- name: Commit stats
run: |
git add stats/
git commit -m "Weekly rtk stats"
git push
```
### Slack Bot
```python
import subprocess
import json
import requests
def send_rtk_stats():
result = subprocess.run(['rtk', 'gain', '--format', 'json'],
capture_output=True, text=True)
data = json.loads(result.stdout)
message = f"""
📊 *RTK Token Savings Report*
Total Saved: {data['summary']['total_saved']:,} tokens
Savings Rate: {data['summary']['avg_savings_pct']:.1f}%
Commands: {data['summary']['total_commands']}
"""
requests.post(SLACK_WEBHOOK_URL, json={'text': message})
```
## Troubleshooting
### No data showing
```bash
# Check if database exists
ls -lh ~/.local/share/rtk/history.db
# Check record count
sqlite3 ~/.local/share/rtk/history.db "SELECT COUNT(*) FROM commands"
# Run a tracked command to generate data
rtk git status
```
### Export fails
```bash
# Check for pipe errors
rtk gain --format json 2>&1 | tee /tmp/rtk-debug.log | jq .
# Use release build to avoid warnings
cargo build --release
./target/release/rtk gain --format json
```
### Incorrect statistics
Token estimation is a heuristic. For precise measurements:
```bash
# Install tiktoken
pip install tiktoken
# Validate estimation
rtk git status > output.txt
python -c "
import tiktoken
enc = tiktoken.get_encoding('cl100k_base')
text = open('output.txt').read()
print(f'Actual tokens: {len(enc.encode(text))}')
print(f'rtk estimate: {len(text) // 4}')
"
```
## Best Practices
1. **Regular Exports**: `rtk gain --all --format json > monthly-$(date +%Y%m).json`
2. **Trend Analysis**: Compare week-over-week savings to identify optimization opportunities
3. **Command Profiling**: Use `--history` to see which commands save the most
4. **Backup Before Cleanup**: Always backup before manual database operations
5. **CI Integration**: Track savings across team in shared dashboards
## See Also
- [README.md](../README.md) - Full rtk documentation
- [CLAUDE.md](../CLAUDE.md) - Claude Code integration guide
- [ARCHITECTURE.md](../contributing/ARCHITECTURE.md) - Technical architecture