872 stars, 15 downloads: how a Linux "AI usage control center" grew inside a Delhi university

Veronica is a desktop app for Ubuntu that focuses on tracking locally how much you've used Claude, Codex, and Cursor and how close you are to your limits, and bundles clipboard, emoji, media, calendar, and a handful of other small tools. In early November it gained over 700 stars in six days, which looks like a new project taking off. Tracing the forks back to their accounts shows otherwise: what grew was a student society at a Delhi university, not users. This piece lays out where the stars came from, where the product actually stands, and what you can take from it.

Nov 5 afternoon, a batch of new Delhi accounts

On Nov 5 of 2026, starting around UTC 10:25 (about 3pm India time), people began forking the repo one after another on GitHub, at 13 to 26 per hour, continuing into the Indian evening. That day saw 80 forks in total. A wave had already hit two days earlier, on the night of Nov 3 (India time 8 to 11), with 18 forks. Before that, the repo, two and a half months old, had only 2 forks in total, one of them from the author of the macOS app it ports.

Going through the accounts behind the latest 100 forks (on GitHub, 11-06):

• 81 have 0 followers each;
• Of 46 accounts, only 2 repo each: this fork, plus the auto-generated GitHub profile repo;
• 14 were registered on the very day of the fork;
• Registration dates cluster in 2026 8 and September, the start of the Indian university academic year; many usernames contain 2007, 2008, 2009, plus the suffixes GitHub auto-appends to duplicate names (-sys, -cmyk, -a11y, -dotcom);
• Those with a location filled in are all in Delhi, Gurugram, or Faridabad, the Delhi capital region.

That's a freshman's brand-new GitHub account. Stars and forks climbed together: from the afternoon of Nov 5 to Nov 6, someone hit star every hour, 11-06 added 352 in a single day.

Who's behind it

The author is Naman Dadhich, a computer science student at Maharaja Surajmal Institute of Technology (MSIT) in New Delhi, class of 2027. His personal site says he is head of development at Geek Room Community MSIT, previously head of development for the MSIT chapter of GDG (Google Developer Groups) and now its lead advisor, and that he has run MLH-backed hackathons. Geek Room began as a WhatsApp group of MSIT students and its website claims 150k+ members.

A society officer, a batch of new accounts registered in the same city and the same semester, forking and starring over two evenings. The most likely explanation is a society event or workshop: freshmen signing up for GitHub on the spot, forking a repo, starring it, and learning the open-source workflow. I couldn't find a public event page or post for a specific session (unverified), but the account profiles and timing already point in that direction.

Beyond that, there's almost no buzz: the author, Sep 20, posted a teaser on X, "Veronica is on its way to Ubuntu…", and no big account reposted it. Reddit, Hacker News, and tech media have no posts about it. Where the 163 stars before Nov 1 came from is unclear; the likely guess is the author's own circle.

stars and downloads are two orders of magnitude apart

(GitHub daily records are logged once a day in Beijing time, so the fork wave on the evening of 11-03 is recorded under 11-04.)

Now look at the people who actually installed it. The README's recommended install is a one-line script that pulls the .deb from GitHub releases, so release download counts are roughly install counts. The latest version, v0.1.19 (released 11-01), has been downloaded 15 times, and v0.1.10 through v0.1.19 across the ten versions total about 105 (GitHub releases, 11-06). Flatpak goes through the author's own repo and isn't counted, so that part can't be verified. Repo watchers: 1. Contributors: just the author, with 190 commits.

872 stars for 15 downloads. The people who starred it didn't go install it.

The product itself: a Linux port of a macOS app

The README's first line is blunt: "Veronica is the Linux port of Edith." Edith (pulkitxm/edith) is a control center for macOS. Veronica copies its feature list, limit calculations, and usage data format, and even the alert copy says "Edith's wording, verbatim." Only the system-call layer was rewritten for Linux. Edith itself has 7 stars on GitHub.

There's plenty of careful work here:

• Risk based on pacing, not just percentage: "A window that's used 60% with a few minutes left matters more than one used 80% with a week left." Each limit ring shows how far ahead of a steady burn rate you are.
• Alerts that don't spam: each threshold fires once, the same notification updates in place, restarts don't re-send, and you can get a heads-up before a reset.
• Shareable usage cards: export a usage calendar or your busiest day as a PNG. It deliberately leaves out repo names, folder paths, chat titles, and dollar amounts. In the README's words, those four things would leak your clients, employer, or income.
• Packaging is complete: an apt install script, an AppImage, a self-signed Flatpak repo, and a GNOME top-bar "notch."

But none of this is why it took off. The download numbers already show that almost nobody was drawn in by these features.

Who it's competing with

"Viewing AI coding tool usage locally" has been one of the most crowded small open-source niches since 2025 (GitHub stars, as of around 11-06):

A Linux user who wants usage visibility can install a GNOME extension or run one ccusage command. Veronica's only clear difference is "one app that bundles everything," and Edith, the macOS original of that form, has only 7 stars. Nobody has validated it.

What you can take from this

Three takeaways, and the first two are genuinely useful:

1. Club mobilization can push a new repo from zero to a few hundred stars, but it can only push stars. A student club of a few dozen to a hundred people can produce a single-day +352 in two evenings. The catch is that those stars never turned into users, and the account profiles give it away: 0 followers, two repos, created the same day, same city.
2. A privacy-safe share card is a small but good distribution design. The most natural spread for usage-stats tools is users posting their charts. Stripping repo names, paths, and dollar amounts first lowers the barrier to posting. Any similar tool can copy this.
3. Porting a macOS tool to Linux is cheap, but pick an original that has already taken off. Porting a 7-star original just means rebuilding a form nobody has validated.

If it were you

The bottom line: this repo's stars weren't earned by the product. The product sits in a niche that already has several projects with 20,000–30,000 stars and a row of GNOME extensions. Worth knowing about, but not worth copying.

Who it's for: if you're in a student tech club or developer community and want a benchmark for how many people it takes to get a new repo to a few hundred stars, this is a ready-made reference. If you're building an AI usage tool, you can borrow its share card and its pacing-based risk model.

Who it's not for: anyone planning to build "yet another AI usage monitor" to chase stars. The top of the niche belongs to famous authors like steipete and early projects like claude-hud, and latecomers split what's left.

How to do it: if you really want to work in this area, don't build a do-everything control center. Find the slice the leaders don't cover. Examples: team-level tracking (several people sharing one account's quota, who used how much), or models usable in China (DeepSeek, Kimi, Tongyi usage and limits; as far as I can tell, no one is focused on these). If you port, pick an original like CodexBar, which has already proven there's demand, not Edith.

How to get users: club members and classmates can supply your first stars, but don't expect that to bring real users once you hit GitHub trending. Real users come from people on X and Reddit who use Claude Code or Codex posting their charts. So make the share card good first, then post an image with a one-line install command in places like r/ClaudeAI and r/linux.

When it was the window: there was no real window. This niche was getting crowded by mid-2025. Anthropic's and OpenAI's own clients increasingly show usage and limits directly, so the case for this whole category is getting thinner.

What would show this analysis is wrong: (1) Over the next two or three weeks, Veronica's per-release downloads rise from a dozen to several hundred. That would mean the club-driven stars got it onto trending and earned real users, and the "mobilize first, then ride trending" path works better than I think. (2) A dedicated AI-usage project appears on Linux with no club and no famous author, and grows to a thousand stars on its own. That would mean Linux really lacks this and is worth entering. (3) The reverse: a month from now, Veronica's stars have stalled and downloads are still single digits. That's the call made in this piece.

Data and sources

GitHub repo page, README, release download counts, fork list and account info (11-06); GitHub daily star/fork records (11-01 to 11-06); namandadhich.dev (author identity and club role); geekroom.co.in (community origin and size, self-reported); pulkitxm/edith repo page; the X posts from @namannn04 9-20 (search snippets); competitor star counts as of 11-06, with "about" marking rounded figures; the specific club event was not verified.