Your AI-tool usage is invisible. Here are 4 tiny local tools to see it.

A developer built four open-source, local-only tools to analyze AI tool usage and costs after discovering that vendor dashboards provide little insight. The tools, available on GitHub, read local data without sending it anywhere and revealed that prompt caching, not input length, dominated the developer's Claude Code spending. The tools include tokenops for cost breakdowns and ccwrapped for shareable usage cards.

You use Claude Code, or ChatGPT, or both, every day. Quick question: how many messages did you send last month? Which model ate most of your budget? How much did prompt caching actually save you? You don't know. I didn't either. That's a weird gap. We instrument everything else — git activity, deploy frequency, test coverage — but the tool we now spend the most hours inside is a black box. The vendor dashboard, if it exists, is a billing page, not a mirror. So I built four tiny tools to fix that for myself. They all run 100% locally . No accounts, no API keys, no telemetry, no network calls. They read files that are already on your disk and print something you can look at. All four are open source on github.com/greymoth-jp https://github.com/greymoth-jp — and because that's a real claim, the only thing I'll ask is that you grep the source yourself before you trust me. Here's the privacy point up front, because it's the whole design: these read your data, but your data never leaves your machine. That's not a feature I'm bolting on for a marketing line. It's the reason the tools are small enough to audit in one sitting. Before the tools, here's what I assumed: my Claude Code bill is dominated by the prompts I write, so to spend less I should write tighter prompts. Compress the context. Trim the system message. The usual advice. I ran the numbers on my own ~/.claude transcripts and got this: | component | share of cost | |---|---| | cacheRead | 72% | | cacheWrite | ~19% | | output | the rest | input | ~0.3% | Input — the thing everyone tells you to compress — was 0.3% of my spend. Compressing my prompts to save money would've been optimizing the rounding error. Worse: compressing a static prompt changes its bytes, which busts the prefix cache, which can make the bill go up . The real cost center was cache reads: long sessions dragging a fat context forward, turn after turn. That points at completely different levers — cache hygiene milestone /compact , /clear before the context balloons, keeping CLAUDE.md static so it doesn't bust the cache , and routing a whole mechanical session to a cheaper tier at the boundary , never mid-session. Important honesty caveat: that 72% is my number, from my usage, and the dollar figures are estimates against published rates. Yours will be different. If you're on a Max/Pro plan it's "value extracted," not literal spend. The point isn't the specific percentage — it's that you can't reason about a cost you've never measured. Measure first, then optimize. The tool below does the measuring. All open source, all local, all MIT-licensed. Two are npm CLIs; one is a browser extension; one reads public data only. tokenops — Claude Code cost truth The one that produced the table above. It reads ~/.claude , breaks your spend down by component and by model, and then gives you data-validated advice — not generic tips, but actions ranked by the dollars your profile says are on the table. npx @greymoth/tokenops demo synthetic data — try it with zero risk first npm i -g @greymoth/tokenops tokenops report cost by component + by model tokenops advise prioritized, $-quantified actions tokenops card a shareable Before→After card --anon hides project names → github.com/greymoth-jp/tokenops · npm: @greymoth/tokenops Start with tokenops demo — it runs on synthetic data so you can see exactly what it does before pointing it at your own transcripts. ccwrapped — your Claude Code "Wrapped" card Same ~/.claude data, different job. Where tokenops is the spreadsheet, ccwrapped is the poster: messages, estimated value, top model, top project, and how much caching saved you — rendered as a self-contained SVG you can screenshot and share. npm i -g @greymoth/ccwrapped ccwrapped --wrapped writes an SVG — open in a browser, screenshot, share ccwrapped --wrapped --anon same, with project names hidden for a clean public share → github.com/greymoth-jp/ccwrapped · npm: @greymoth/ccwrapped My own card said ~194,379 messages and a prompt-caching figure in the six figures of estimated equivalent value. Again — that's my year, not a benchmark. The fun part is that yours is a surprise even to you. inkdex — ChatGPT + Claude usage, in the browser Not everyone lives in a terminal. inkdex is a Manifest V3 browser extension that tracks your ChatGPT and Claude web usage locally and prints a risograph Wrapped card. No account, and nothing leaves your browser — it's all in extension storage. → github.com/greymoth-jp/inkdex https://github.com/greymoth-jp/inkdex ghwrapped — any public GitHub profile → a shareable card The odd one out: it doesn't read your private data because it doesn't need to. Feed it any public GitHub username and it renders a risograph Wrapped card from public data only . Good for a year-in-review, a profile README, or sizing up a repo you're about to depend on. → github.com/greymoth-jp/ghwrapped https://github.com/greymoth-jp/ghwrapped I keep saying these send nothing. You shouldn't take that on faith from a stranger on the internet — that's the entire point of shipping the source. So: bin/ in grep -rEi 'fetch|http|net\.|request|axios' . in the cloned repo. If a usage analyzer is opening a socket, you'll see it.That's the difference between trust me and verify me , and it's the only kind of privacy claim worth making. Here's the actual ask, and it's the fun one: npm i -g @greymoth/ccwrapped ccwrapped --wrapped --anon the --anon hides your project names, so it's safe to post I genuinely want to see the spread. My caching savings looked absurd; maybe yours dwarf mine, maybe you barely cache at all and that itself is the finding. Either way you'll learn something about a tool you use every day and have never actually looked at. And if you find a bug, or a place where one of these does touch the network when it shouldn't — open an issue. Catching that is the best possible outcome, because it proves the "grep it yourself" model works. Repos, one more time, all under one roof: github.com/greymoth-jp → ccwrapped , tokenops , inkdex , ghwrapped .Go measure the thing you can't see. Then come back and show me the card.