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tokenmeter

Track AI token usage and costs across providers. Import sessions, view dashboard, costs breakdown, and compare Max plan savings.

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name: tokenmeter description: "Track AI token usage and costs across providers. Import sessions, view dashboard, costs breakdown, and compare Max plan savings." user-invocable: true metadata: {"openclaw":{"emoji":"๐Ÿ“Š"}}

tokenmeter - AI Usage & Cost Tracking for OpenClaw

Track your AI token usage and costs across all providers โ€” locally, privately.

Slash Command Examples

  • /tokenmeter โ€” show today's dashboard
  • /tokenmeter how much did we spend this week? โ€” weekly cost report
  • /tokenmeter costs breakdown by model โ€” model split analysis
  • /tokenmeter import latest sessions โ€” pull in new usage data
  • /tokenmeter compare max plan savings โ€” show API vs subscription savings

Overview

tokenmeter is a CLI tool that tracks LLM API usage and calculates real-time cost estimates. For OpenClaw users on the Claude Max plan, it helps:

  1. Prove Max plan value - Show what you would have paid on API billing
  2. Monitor usage patterns - Understand which models you use most
  3. Catch overages early - Know if you're using expensive models too much
  4. Unified tracking - Track usage across multiple OpenClaw instances

All data stays local (SQLite at ~/.tokenmeter/usage.db). No telemetry, no cloud sync.


Installation

The bot handles everything automatically.

When first needed, the bot will:

# 1. Clone repo if it doesn't exist
if [ ! -d ~/clawd/tokenmeter ]; then
  cd ~/clawd
  git clone https://github.com/jugaad-lab/tokenmeter.git
fi

# 2. Setup Python venv if it doesn't exist
cd ~/clawd/tokenmeter
if [ ! -d ".venv" ]; then
  python3 -m venv .venv
  source .venv/bin/activate
  pip install -e .
fi

# 3. Activate and use
source .venv/bin/activate
tokenmeter import --auto

After first setup: Bot just activates venv and runs commands.

No admin action needed - the bot clones, installs, and configures automatically when you first ask it to check usage or costs.


How the Bot Uses This Tool

When You Ask: "How much did I spend this week?"

Step 1: Bot reads this SKILL.md

  • Skill matching triggers on keywords: "spend", "cost", "usage", "tokens"
  • Bot loads this entire file into context

Step 2: Bot checks if tokenmeter exists

if [ ! -d ~/clawd/tokenmeter ]; then
  cd ~/clawd
  git clone https://github.com/jugaad-lab/tokenmeter.git
  cd tokenmeter
  python3 -m venv .venv
  source .venv/bin/activate
  pip install -e .
fi

Step 3: Bot imports latest usage

cd ~/clawd/tokenmeter
source .venv/bin/activate
tokenmeter import --auto

This reads all OpenClaw session files and logs them to the database.

Step 4: Bot runs the appropriate command

tokenmeter costs --period week

Step 5: Bot parses the output

Model                    Cost      % of Total
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
anthropic/claude-opus-4  $741.95   65.0%
anthropic/claude-sonnet-4 $400.26  35.0%
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
Total                    $1,142.22

Step 6: Bot responds to you in plain English

"You spent $1,142 this week (API-equivalent). Opus cost $742 (65%), Sonnet cost $400 (35%). Your Max plan ($100/month = ~$25/week) saved you $1,117 this week."


Bot Command Reference

Standard pattern:

cd ~/clawd/tokenmeter && source .venv/bin/activate && tokenmeter [command]

Common commands the bot will use:

# Import latest usage
tokenmeter import --auto

# Quick overview
tokenmeter dashboard

# Weekly breakdown
tokenmeter costs --period week

# Monthly summary
tokenmeter summary --period month

Usage

Quick Commands

# Discover session sources (OpenClaw, Claude Code, etc.)
tokenmeter scan

# Import all discovered sessions
tokenmeter import --auto

# Preview import without writing
tokenmeter import --auto --dry-run

# Show today's usage
tokenmeter dashboard

# Weekly summary
tokenmeter summary --period week

# Cost breakdown by model
tokenmeter costs --period month

# List all supported models + pricing
tokenmeter models

# View recent history
tokenmeter history --limit 20

Integration with OpenClaw

Automatic Import (Recommended)

OpenClaw writes token usage to session JSONL files at:

~/.clawdbot/agents/*/sessions/*.jsonl

Step 1: Discover session sources

cd ~/clawd/tokenmeter
source .venv/bin/activate
tokenmeter scan

This shows all discovered session directories:

  • .clawdbot/agents/main/sessions/ (OpenClaw)
  • .claude/projects/*/sessions/ (Claude Code)
  • Any other compatible session formats

Step 2: Import all at once

tokenmeter import --auto

This will:

  • Parse all discovered session files
  • Extract token usage from each LLM call
  • Log to tokenmeter with API-equivalent costs
  • Skip already-imported entries (idempotent)
  • Show total records and cost

Options:

tokenmeter import --auto --dry-run  # Preview without writing
tokenmeter import --path ~/.clawdbot/agents/main/sessions/  # Import specific directory

Recommended: Run tokenmeter import --auto daily via cron or manually after heavy usage.

Manual Logging (Fallback)

If you need to log usage manually:

tokenmeter log \
  --provider anthropic \
  --model claude-sonnet-4 \
  --input 1500 \
  --output 500 \
  --app openclaw

Options:

  • --provider / -p: anthropic, openai, google, azure
  • --model / -m: Model name (see tokenmeter models)
  • --input / -i: Input tokens
  • --output / -o: Output tokens
  • --app / -a: Application name (e.g., "openclaw")

Understanding the Data

Model Pricing (as of Feb 2026)

Token Typeclaude-sonnet-4claude-opus-4claude-3.5-haiku
Input$3.00/1M$15.00/1M$0.80/1M
Output$15.00/1M$75.00/1M$4.00/1M
Cache Write$3.75/1M$18.75/1M$1.00/1M
Cache Read$0.30/1M$1.50/1M$0.08/1M

Understanding Cache Tokens

What are cache tokens?

OpenClaw (and Claude) use prompt caching to store parts of your conversation in memory. This means you don't send the same context repeatedly.

Two types of cache tokens:

  1. Cache WRITE tokens - Tokens sent ONCE and stored in cache

    • Example: Your entire codebase, documentation, system prompts
    • Slightly more expensive than regular input (~25% markup)
    • Only paid once, then reused for free (almost)
  2. Cache READ tokens - Tokens reused from cache

    • You're NOT sending these again - Claude reads them from memory
    • 90% cheaper than regular input tokens
    • This is where massive savings come from

Real example from our usage:

This Month:
Regular Input:    119.5K tokens  ($0.36)
Regular Output:     3.8M tokens  ($57.00)
Cache Write:      157.2M tokens  ($589.50 - paid once)
Cache Read:     1,024.3M tokens  ($307.29 - 90% discount!)
Total: $954.15

Without caching, we'd send ~1.2 BILLION tokens as regular input ($3,600+). With caching: We only pay $307 for those cache reads.

Savings: $3,293 from caching alone this month! ๐ŸŽ‰

Reading the Dashboard

โ•ญโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€ tokenmeter โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ•ฎ
โ”‚  TODAY  $122.42  (396.9K tokens)                 โ”‚
โ”‚  WEEK  $1142.22  (3.4M tokens)                   โ”‚
โ•ฐโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ•ฏ

Provider   Input   Output  Cache R  Cache W  Total    Cost
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
Anthropic  12.2K   384.7K  116.4M   13.1M    396.9K   $122.42

Reading the columns:

  • Input: Fresh tokens sent to Claude
  • Output: Tokens Claude generated
  • Cache R: Tokens reused from cache (READ)
  • Cache W: Tokens written to cache (WRITE)
  • Total: Input + Output (regular tokens only)
  • Cost: API-equivalent cost

Why Cache R is so large: Every time you continue a conversation, Claude reads your entire context from cache instead of you sending it fresh. Over many turns, this adds up to billions of tokens reused.

Cost breakdown:

  • Regular tokens: Expensive ($3-15 per 1M)
  • Cache Write: Slightly more expensive (~25% markup)
  • Cache Read: 90% cheaper ($0.30-1.50 per 1M)

This is why the cost stays low despite huge cache numbers.

Comparing to Claude Max Plan

Your Max plan: $100/month flat rate

If tokenmeter shows $800 this month:

  • API-equivalent cost: $800
  • Max plan cost: $100
  • Savings: $700 โœ…

If tokenmeter shows $90 this month:

  • API-equivalent cost: $90
  • Max plan cost: $100
  • Overpaying by $10 (but you get peace of mind!)

Workflows

Daily Check-In

cd ~/clawd/tokenmeter
source .venv/bin/activate

# Import latest usage
tokenmeter import --auto

# Quick overview
tokenmeter dashboard

Weekly Review

tokenmeter summary --period week
tokenmeter costs --period week

Look for:

  • Heavy Opus usage (expensive!)
  • Unusual spikes
  • High output token counts (code generation, long responses)

Monthly Billing Comparison

At month end:

tokenmeter costs --period month

Compare to your Anthropic invoice:

  • Max plan: $100 flat
  • API-equivalent (tokenmeter): $XXX
  • Delta = savings (or loss)

Cron Automation (Optional)

Add to your HEARTBEAT.md or run via cron:

# Run daily at 11 PM
0 23 * * * cd ~/clawd/tokenmeter && source .venv/bin/activate && tokenmeter import --auto

This keeps tokenmeter in sync without manual effort.


Multi-Bot Tracking

If you run multiple OpenClaw instances (e.g., Cheenu + Chhotu):

  1. Both bots import to tokenmeter on their respective machines
  2. Each uses --app flag to distinguish:
    tokenmeter log -p anthropic -m claude-sonnet-4 -i 1000 -o 500 --app cheenu
    tokenmeter log -p anthropic -m claude-sonnet-4 -i 800 -o 400 --app chhotu
    
  3. Nagaconda can aggregate reports from both to see total team usage

Troubleshooting

"tokenmeter: command not found"

Activate the virtual environment:

cd ~/clawd/skills/tokenmeter
source .venv/bin/activate

Empty dashboard after import

Check:

  1. OpenClaw session files exist: ls ~/.clawdbot/agents/*/sessions/*.jsonl
  2. Import command ran successfully (no errors)
  3. Database has entries: sqlite3 ~/.tokenmeter/usage.db "SELECT COUNT(*) FROM usage;"

Prices seem wrong

Pricing is based on API rates as of Feb 2026. If Anthropic changes pricing, update tokenmeter/pricing.py or open an issue on GitHub.


Examples

Example 1: Check today's usage

$ tokenmeter dashboard
โ•ญโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€ tokenmeter โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ•ฎ
โ”‚  TODAY  $4.23  (141,000 tokens)                  โ”‚
โ”‚  WEEK   $28.90  (963,000 tokens)                 โ”‚
โ•ฐโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ•ฏ

Analysis: $4.23 today, trending toward ~$30/week. Well within Max plan ($100/mo).

Example 2: Weekly cost breakdown

$ tokenmeter costs --period week

Provider   Model              Input      Output     Cost      %
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
Anthropic  claude-sonnet-4    450K       180K       $4.05    45%
Anthropic  claude-opus-4       90K        30K       $3.60    40%
Anthropic  claude-3.5-haiku   800K       200K       $1.44    15%
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
Total                        1,340K      410K       $9.09   100%

Analysis: Using Opus for 40% of costs but only ~7% of token volume. Consider using Sonnet more.

Example 3: Month-end comparison (Real Data - Feb 2026)

$ tokenmeter import --auto
Imported 13,713 records
Total cost: $1,246.55

$ tokenmeter costs --period month

Model                    Input   Output    Cost      % of Total
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
anthropic/claude-opus-4  47.3K   1.6M      $743.35   59.6%
anthropic/claude-sonnet-4 70.8K  2.2M      $501.75   40.3%
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
Total                    118.8K  3.8M      $1,246.55 100%

$ tokenmeter summary --period month

Provider   Input    Output   Total    Cost        Requests
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
Anthropic  118.8K   3.8M     3.9M     $1,246.55   12,552

Analysis:

  • API-equivalent cost: $1,246.55
  • Max plan cost: $100.00
  • Savings: $1,146.55 โœ…

Opus usage (59.6% of cost) shows heavy extended-thinking use. Max plan absolutely paid for itself this month!


FAQ

Q: Does tokenmeter send data anywhere? A: No. Everything is stored locally in ~/.tokenmeter/usage.db. Zero telemetry.

Q: What if I delete the database? A: You lose history, but can rebuild by re-importing OpenClaw sessions (idempotent).

Q: Can I use this with non-OpenClaw tools? A: Yes! It supports Claude Code, Cursor, and manual logging for any LLM tool.

Q: Will this slow down OpenClaw? A: No. Import runs separately and reads logs after-the-fact.

Q: What about cache tokens? A: tokenmeter includes cache read/write tokens in its calculations (OpenClaw tracks them).


References


Changelog

2026-02-06 (v2)

  • โœ… tokenmeter scan - Auto-discover session sources
  • โœ… tokenmeter import --auto - Import all discovered sessions
  • โœ… Real data example showing $1,146 monthly savings on Max plan
  • โœ… Updated workflows with new commands
  • โœ… Tested on actual OpenClaw + Claude Code sessions

2026-02-06 (v1)

  • Initial skill creation
  • Documented installation and usage
  • Added workflow examples

Built to answer the question: "How much is my Max plan really saving me?" ๐Ÿ’ฐ

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