{"id":"c510d594-d67a-45ae-86f4-35f3bc3839f2","shortId":"rPvTjg","kind":"skill","title":"Monitor coding-agent token spend with Splitrail","tagline":"Track token burn, spend, and model mix across multiple coding-agent tools from one local monitoring workflow.","description":"# Monitor coding-agent token spend with Splitrail\n\nTrack token burn, spend, and model mix across multiple coding-agent tools from one local monitoring workflow.\n\n## Prerequisites\n\nSplitrail binary, local agent usage logs or supported agent installations\n\n## Installation\n\nUse the upstream install or setup path that matches your environment:\n- cargo run\n\nBasic usage or getting-started notes:\n- Splitrail is a **fast, cross-platform, real-time token usage tracker and cost monitor for**:\n- 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](https://splitrail.dev) for safe-keeping and cross-machine usage aggregati...\n- Splitrail can run as an [MCP (Model Context Protocol)](https://modelcontextprotocol.io/) server, allowing AI assistants to query your usage statistics programmatically.\n\n- Source: https://github.com/Piebald-AI/splitrail\n- Extracted from upstream docs: https://raw.githubusercontent.com/Piebald-AI/splitrail/HEAD/README.md\n\n## Documentation\n\n- https://github.com/Piebald-AI/splitrail\n\n## Source\n\n- [Agent Skill 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