Overview
- Skill Key
- cheenu1092-oss/tokenmeter
- Author
- cheenu1092-oss
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/cheenu1092-oss/tokenmeter
- Latest Commit SHA
- e908bf44ede20a7103793640033554ade6b7ad5f
Track AI token usage and costs across providers. Import sessions, view dashboard, costs breakdown, and compare Max plan savings.
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直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 tokenmeter 技能。 若已安装,则直接安装 tokenmeter 技能。
# tokenmeter - AI Usage & Cost Tracking for OpenClaw Track your AI token usage and costs across all providers — locally, privately. ## Slash Command Examples - `/tokenmeter` — show today's dashboard - `/tokenmeter how much did we spend this week?` — weekly cost report - `/tokenmeter costs breakdown by model` — model split analysis - `/tokenmeter import latest sessions` — pull in new usage data - `/tokenmeter compare max plan savings` — 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: ```bash # 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 tokenme...
<p align="center"> <img src="assets/logo.png" alt="tokenmeter logo" width="200" /> </p> # 🪙 tokenmeter **Track your AI API usage and costs across all providers — locally, privately.**   ## Why This Exists You're using Claude Code, Cursor, ChatGPT, Azure OpenAI, and a dozen other AI tools. Your monthly bill is a mystery until it arrives. Sound familiar? **tokenmeter** solves this by: - 📊 Tracking token usage across OpenAI, Anthropic, Azure OpenAI, and Google - 💰 Calculating real-time cost estimates based on current pricing - 🔒 Running 100% locally — your data never leaves your machine - 📈 Showing trends and breakdowns by model, day, and application ## Installation ```bash pip install tokenmeter # or pipx install tokenmeter ``` ## Quick Start ```bash # Log a usage event manually tokenmeter log --provider anthropic --model claude-sonnet-4 --input 1500 --output 500 # Import from Claude Code's usage file tokenmeter import claude-code # Show today's summary tokenmeter summary # Show cost breakdown tokenmeter costs --period week # Interactive dashboard tokenmeter dashboard ``` ## Features ### 🎯 Multi-Provider Support - **Anthropic** (Claude 3.5, 4, Opus, Sonnet, Haiku) - **OpenAI** (GPT-4, GPT-4o, o1, o3) - **Azure OpenAI** (all deployed models) - **Google** (Gemini Pro, Ultra, Flash) ### 📊 Rich CLI Dashboard with Cache Tracking ``` ╭─────────────────── tokenmeter ───────────────────╮ │ TODAY $122.42 (396.9K tokens) │ │ WEEK $1142.22 (3.4M tokens) │ ╰──────────────────────────────────────────────────╯ Provider Input Output Cache R Cache W Total Cost ─────────────────────────────────────────────────────────── Anthropic 12.2K 384.7K 116.4M 13.1M 396.9K $122.42 ``` **Cache R** and **Cache W** show prompt caching usage: - **Cache Write**: Tokens stored in ca...
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