Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Productivity
tokenmeter
Track AI token usage and costs across providers. Import sessions, view dashboard, costs breakdown, and compare Max plan savings.
skill openclawclawhub Free
Track AI token usage and costs across providers. Import sessions, view dashboard, costs breakdown, and compare Max plan savings.
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Documentation
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: Prove Max plan value - Show what you would have paid on API billing Monitor usage patterns - Understand which models you use most Catch overages early - Know if you're using expensive models too much 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.
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 โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ anthropic/claude-opus-4 $741.95 65.0% anthropic/claude-sonnet-4 $400.26 35.0% โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ 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
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
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")
Model Pricing (as of Feb 2026)
Token Typeclaude-sonnet-4claude-opus-4claude-3.5-haikuInput$3.00/1M$15.00/1M$0.80/1MOutput$15.00/1M$75.00/1M$4.00/1MCache Write$3.75/1M$18.75/1M$1.00/1MCache 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: 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) 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! ๐
Reading the Dashboard
โญโโโโโโโโโโโโโโโโโโโ tokenmeter โโโโโโโโโโโโโโโโโโโโฎ โ TODAY $122.42 (396.9K tokens) โ โ WEEK $1142.22 (3.4M tokens) โ โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏ Provider Input Output Cache R Cache W Total Cost โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ 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 โ If tokenmeter shows $90 this month: API-equivalent cost: $90 Max plan cost: $100 Overpaying by $10 (but you get peace of mind!)
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): Both bots import to tokenmeter on their respective machines 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 Nagaconda can aggregate reports from both to see total team usage
"tokenmeter: command not found"
Activate the virtual environment: cd ~/clawd/skills/tokenmeter source .venv/bin/activate
Empty dashboard after import
Check: OpenClaw session files exist: ls ~/.clawdbot/agents/*/sessions/*.jsonl Import command ran successfully (no errors) 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.
Example 1: Check today's usage
$ tokenmeter dashboard โญโโโโโโโโโโโโโโโโโโโ tokenmeter โโโโโโโโโโโโโโโโโโโโฎ โ TODAY $4.23 (141,000 tokens) โ โ WEEK $28.90 (963,000 tokens) โ โฐโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฏ 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 % โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ 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% โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ 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 โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ anthropic/claude-opus-4 47.3K 1.6M $743.35 59.6% anthropic/claude-sonnet-4 70.8K 2.2M $501.75 40.3% โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ Total 118.8K 3.8M $1,246.55 100% $ tokenmeter summary --period month Provider Input Output Total Cost Requests โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ 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 โ 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
GitHub: https://github.com/jugaad-lab/tokenmeter OpenClaw Docs: https://docs.openclaw.ai Anthropic Pricing: https://anthropic.com/pricing
2026-02-06 (v2)
โ tokenmeter scan - Auto-discover session sources โ tokenmeter import --auto - Import all discovered sessions โ Real data example showing $1,146 monthly savings on Max plan โ Updated workflows with new commands โ 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?" ๐ฐ
Category context
Workflow acceleration for inboxes, docs, calendars, planning, and execution loops.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
4 Docs2 Scripts
- SKILL.md
- QUICKREF.md
- README.md
- TASK.md
- examples/daily-report.sh
- examples/test-installation.sh