Every dollar my agents spent,
one pane of glass.
A single Python file that reads every JSONL log my AI stack writes — across Anthropic, OpenAI, and Google — and renders a live dashboard with 5-second refresh. I built it because nothing off-the-shelf tracked all three.
No tool tracks spend across providers.
My fleet runs on three providers: Anthropic for Claude Code, OpenAI for my personal agent Ari, and Google for Rex. Each vendor gives you a usage dashboard for their own bill — and nothing else.
I needed one pane of glass to see it all, with real-time burn, cache hit rates, and a per-project breakdown of where the money is going. So I wrote one in an hour.
Real numbers, not provider approximations.
The dashboard parses raw JSONL logs and computes cost using Anthropic's published 1-hour cache pricing — which is 2× what tools like ccusage assume. My totals match the Anthropic console.
One Python file, zero dependencies.
python3 dashboard.py
and a browser tab. That's the whole ship.
.jsonl to ~/.claude/projects/ every session. Dedupe by Anthropic message.id to avoid double-counting.~/.openclaw/agents/main/sessions/. Cost is pre-computed per message in the log.ssh's in and runs hermes insights every 5 minutes, caches the result.http.server. Serves /api/stats as JSON + single-page / HTML.Chart.js via CDN. Polls /api/stats every 5 seconds. No build step.python3 dashboard.py — launches server on port 8765 and opens the browser. One file, no config.You can't optimize what you don't measure.
True cost per project
See which project burns Opus and which uses Sonnet. Route cheap tasks to Haiku, save thousands a month.
Real-time burn rate
Last-hour cost + 5-hour rolling session. You feel the meter running, the way you should.
Cache hit truth
If cache hit drops below 80%, something's wrong with your prompt structure. Dashboard tells you instantly.
Per-project ranking
Top 10 projects by spend, tokens, call count. Shows where to invest engineering time.
Want it?
Drop me a DM — I'll clean it up and release the script. Or wait for the YouTube video where I walk through the whole build.
@heyrexaiagent →