Token Savings Analytics

Token Savings Analytics

rtk gain shows how much bash output RTK has removed across all your commands, with daily, weekly, and monthly breakdowns.

What rtk gain measures is the reduction in bash output bytes, converted to estimated tokens. Bash output is one contributor to input tokens, alongside your prompt, the system prompt and conversation history, and input tokens are in turn only part of the bill, which also counts output tokens. See How RTK Savings Work for the full picture.

Quick reference

# Default summary
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            # all breakdowns at once

# Classic flags
rtk gain --graph          # ASCII graph, last 30 days
rtk gain --history        # last 10 commands
rtk gain --quota          # monthly quota savings estimate (default tier: 20x)
rtk gain --quota -t pro   # use pro tier token budget for estimate
rtk gain --recalls        # recall efficiency per filter (calibration)

# Export
rtk gain --all --format json > savings.json
rtk gain --all --format csv  > savings.csv

Daily breakdown

rtk gain --daily

Example output (illustrative numbers from one machine, not typical results — yours depend entirely on which commands you run):

📅 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%

• Cmds: RTK commands executed
• Input: Estimated tokens from raw command output (bytes / 4)
• Output: Estimated tokens after filtering (bytes / 4)
• Saved: Input - Output, in estimated tokens
• Save%: Saved / Input × 100 — a bash output byte ratio, not a share of your bill

Weekly and monthly breakdowns

rtk gain --weekly
rtk gain --monthly

Same columns as daily, aggregated by Sunday-Saturday week or calendar month.

Export formats

Format	Flag	Use case
text	default	Terminal display
json	--format json	Programmatic analysis, dashboards
csv	--format csv	Excel, Python/R, Google Sheets

JSON structure:

{
  "summary": {
    "total_commands": 196,
    "total_input": 1276098,
    "total_output": 59244,
    "total_saved": 1220217,
    "avg_savings_pct": 95.62
  },
  "daily": [...],
  "weekly": [...],
  "monthly": [...]
}

Typical savings by command

Command	Bash output reduction	Mechanism
git status	77-93%	Compact stat format
eslint	84%	Group by rule
jest	94-99%	Show failures only
vitest	94-99%	Show failures only
find	75%	Tree format
pnpm list	70-90%	Compact dependencies
grep	70%	Truncate + group

These percentages measure bash output bytes removed, not cost reduction.

How token estimation works

rtk gain estimates tokens as bytes / 4 (src/core/tracking.rs:1284). RTK ships no real tokenizer by design: embedding one would cost startup time and would require a tokenizer per model, or a per-session model lookup, which RTK does not implement. The same estimator is applied to raw and filtered output, so the percentage is reliable; the absolute token counts are approximate and will not match your provider’s billing.

Input Tokens  = estimate_tokens(raw_command_output)
Output Tokens = estimate_tokens(rtk_filtered_output)
Saved Tokens  = Input - Output
Savings %     = (Saved / Input) × 100

Database

Savings data is stored locally in SQLite:

• Location: ~/.local/share/rtk/history.db (Linux / macOS)
• Retention: 90 days (automatic cleanup)
• Scope: Global across all projects and Claude sessions

# Inspect raw data
sqlite3 ~/.local/share/rtk/history.db \
  "SELECT timestamp, rtk_cmd, saved_tokens FROM commands
   ORDER BY timestamp DESC LIMIT 10"

# Backup
cp ~/.local/share/rtk/history.db ~/backups/rtk-history-$(date +%Y%m%d).db

# Reset
rm ~/.local/share/rtk/history.db    # recreated on next command

Analysis workflows

# Weekly progress: generate a CSV report every Monday
rtk gain --weekly --format csv > reports/week-$(date +%Y-%W).csv

# Monthly budget review
rtk gain --monthly --format json | jq '.monthly[] |
  {month, saved_tokens, quota_pct: (.saved_tokens / 6000000 * 100)}'

# Cron: daily JSON snapshot for a dashboard
0 0 * * * rtk gain --all --format json > /var/www/dashboard/rtk-stats.json

Python/pandas:

import pandas as pd
import subprocess

result = subprocess.run(['rtk', 'gain', '--all', '--format', 'csv'],
                       capture_output=True, text=True)
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])))
daily_df['date'] = pd.to_datetime(daily_df['date'])
daily_df.plot(x='date', y='savings_pct', kind='line')

GitHub Actions (weekly stats):

on:
  schedule:
    - cron: '0 0 * * 1'
jobs:
  stats:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - run: cargo install --git https://github.com/rtk-ai/rtk --branch master rtk
      - run: rtk gain --weekly --format json > stats/week-$(date +%Y-%W).json
      - run: git add stats/ && git commit -m "Weekly rtk stats" && git push

Quota estimate

--quota expresses the estimated tokens saved as a fraction of a monthly subscription budget. Like every other figure in rtk gain, it is derived from the bytes / 4 estimate of bash output, so treat it as an order of magnitude rather than a billing forecast.

rtk gain --quota          # uses 20x tier by default
rtk gain --quota -t pro   # Claude Pro plan budget
rtk gain --quota -t 5x    # 5× usage plan budget
rtk gain --quota -t 20x   # 20× usage plan budget

The tiers (pro, 5x, 20x) correspond to Anthropic Claude API subscription levels, each with a different monthly token allocation. RTK uses those allocations as a denominator to express your savings as a percentage of your budget.

Find missed savings

rtk gain shows what RTK saved. To find commands that ran without RTK and calculate what you lost, see rtk discover.

Recall efficiency

--recalls measures how often your AI assistant goes back for output a filter elided — the signal that a filter’s cap is too aggressive for your workflow. Every time a filter stores elided output (an elision) and every time the assistant retrieves it (a recall), RTK counts it per filter:

rtk gain --recalls

Recall efficiency  (current mode: sqlite)

SQLITE (exact — reads go through rtk recall)
FILTER                   ELISIONS RECALLED   RATE
vitest                         67       29    43%
docker-images                 142        3     2%

TEE (approximate — bash-observed reads only)
FILTER                   ELISIONS RECALLED   RATE
cargo_test                     38        4   ≥10%

How to read it:

• RATE is the share of elided outputs the assistant went back for. Re-reading the same entry counts once — the rate measures entries consulted, not read commands.
• A high rate (say above 30%) means that filter regularly hides output the assistant needs: every recall is an extra API round-trip you paid for. Consider raising that filter’s cap.
• A low rate means the filter’s cap is well calibrated — the elided output was noise.

The two sections are never merged because the data quality differs:

• SQLITE (exact): reads go through rtk recall <hash>, the only access path, so the count is exact.
• TEE (approximate): in legacy tee mode, reads are shell commands (tail, cat, grep, …) observed by the rewrite hook before execution. Editor or assistant file-tool reads are invisible, denied commands are not counted, and the per-file dedup window is finite — so the ≥ rate is approximate, not exact. A high rate is still a reliable signal that the cap is too aggressive.

Stats survive entry eviction and retention cleanup: calibration data is kept even after the underlying outputs are purged.

Troubleshooting

No data showing:

ls -lh ~/.local/share/rtk/history.db
sqlite3 ~/.local/share/rtk/history.db "SELECT COUNT(*) FROM commands"
git status    # run any tracked command to generate data

Incorrect statistics: Token estimation is a heuristic. For precise counts, use tiktoken:

pip install tiktoken
git status > output.txt
python -c "
import tiktoken
enc = tiktoken.get_encoding('cl100k_base')
print(len(enc.encode(open('output.txt').read())), 'actual tokens')
"