by Piebald-AI
Fast, cross-platform, real-time token usage tracker and cost monitor for Gemini CLI / Claude Code / Codex CLI / Qwen Code / Cline / Roo Code / Kilo Code / GitHub Copilot / OpenCode / Pi Agent / Piebald.
# Add to your Claude Code skills
git clone https://github.com/Piebald-AI/splitrailLast scanned: 5/30/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-05-30T15:45:34.000Z",
"npmAuditRan": true,
"pipAuditRan": true
}splitrail is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by Piebald-AI. Fast, cross-platform, real-time token usage tracker and cost monitor for Gemini CLI / Claude Code / Codex CLI / Qwen Code / Cline / Roo Code / Kilo Code / GitHub Copilot / OpenCode / Pi Agent / Piebald. It has 191 GitHub stars.
Yes. splitrail passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/Piebald-AI/splitrail" and add it to your Claude Code skills directory (see the Installation section above).
splitrail is primarily written in Rust. It is open-source under Piebald-AI on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh splitrail against similar tools.
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We've released Piebald, the ultimate agentic AI developer experience.
Download it and try it out for free! https://piebald.ai/
Scroll down for Splitrail. :point_down:
Splitrail is a fast, cross-platform, real-time token usage tracker and cost monitor for:
Run one command to instantly review all of your CLI coding agent usage. Upload your usage data to your private account on the Splitrail Cloud for safe-keeping and cross-machine usage aggregation. From the team behind Piebald.
[!note] ⭐ If you find Splitrail useful, please consider starring the repository to show your support! ⭐
Download the binary for your platform on the Releases page.
Splitrail can run as an MCP (Model Context Protocol) server, allowing AI assistants to query your usage statistics programmatically.
splitrail mcp
get_daily_stats - Query usage statistics with date filteringget_model_usage - Analyze model usage distributionget_cost_breakdown - Get cost breakdown over a date rangeget_file_operations - Get file operation statisticscompare_tools - Compare usage across different AI coding toolslist_analyzers - List available analyzerssplitrail://summary - Daily summaries across all datessplitrail://models - Model usage breakdownSplitrail stores its configuration at ~/.splitrail.toml:
[server]
url = "https://splitrail.dev"
api_token = "your-api-token"
[upload]
auto_upload = false
upload_today_only = false
[formatting]
number_comma = false
number_human = false
locale = "en"
decimal_places = 2
On Windows, we use lld-link.exe from LLVM to significantly speed up compilation, so you'll need to install it to compile Splitrail. Example for winget:
winget install --id LLVM.LLVM
Then add it to your system PATH:
:: Command prompt
setx /M PATH "%PATH%;C:\Program Files\LLVM\bin\"
set "PATH=%PATH%;C:\Program Files\LLVM\bin"
or
# PowerShell
setx /M PATH "$env:PATH;C:\Program Files\LLVM\bin\"
$env:PATH = "$env:PATH;C:\Program Files\LLVM\bin\"
Then use standard Cargo commands to build and run:
cargo run
Build as normal:
cargo run
Copyright © 2026 Piebald LLC.