Stringers
GitHub open-source project · written 11-6
Ansub/tv-detox · Ansub

Shipped 8 hours late and still got 1M views: how TV Detox rode the "use AI to clean up old TVs" wave

What it is A prompt you paste into Claude Code / Codex, plus a minimal TV home screen. The AI connects to an old Android TV over Wi‑Fi, turns off preinstalled software and ads, swaps in a clean home screen, and everything can be undone.

Why it took off It caught the "AI makes old TVs fast again" topic that someone else had lit up. It came only 8 hours later, was easier to get started with than the original project, and came with a demo video that the recommendation algorithm pushed to 1M views. The Verge named it the day the repo was built.

CHow you can follow this play The TV topic is already crowded, so don't build it. Take its playbook to the next hot topic: follow the same-day viral post immediately, put reproducible prompts, prebuilt packages, and undo scripts in the repo, and add a before-and-after video.

Grade C: the chase-the-hot-topic playbook (fast, with video, easier to start with) is worth learning. But the TV ad-removal topic had dozens of same-topic repos within 10 days, the original project took more than 80% of the attention, and the heat has already passed its peak. Following it now won't get you the stars or the press. Public / widely discussed
Data (updated daily) · Repo created 2026-10-18 · 2,243 stars · 7 days +276
GitHub · stars
01k2k10-1810-2310-2811-0311-082.2k
Data 2026-10-18 → 2026-11-08 (22 days, 22 observations). Points before 10-28 come from deeply / archive backfill, not every day has one

In 2026 Oct 17, a developer posted on X that he had used AI to strip the ads off his parents' TV. The post got 8.6M views. 8 hours later, product builder Ansub Khan posted nearly the same thing about "my parents' old Android TV"; the next day he created a GitHub repo, and that same day posted a 4-minute demo video. The video later reached 1M views, and the repo has 2,192 stars. He wasn't the first to build it, and his star count is only 1/24 of the original project's. What's worth studying is how he followed: faster than others, with video, and with a clear idea of what he wanted beyond stars from the start.

What it is

TV Detox is a prompt plus a minimal TV launcher written in Java. After the user turns on developer mode and USB debugging on the TV, they paste the prompt into Claude Code or Codex on their computer. The AI connects to the TV over Wi‑Fi ADB and, before changing anything, sorts every app into three groups: "safe to disable," "the TV needs it," and "you use it." The AI only acts after the user confirms each item. It disables apps rather than deleting them, logs every step, and generates a one-click undo script. Then it turns off animations and installs a new home screen: a large clock, a row of common apps, and a row of HDMI inputs and settings, with nothing else.

The effect the author reports on his blog (10-24): free memory went from about 370 MB to 600–650 MB. In the YouTube comments, someone reported their own numbers: "Ran it on my JVC TV with Codex, free memory went from 174MB to 356MB."

Why now

这波热潮不是他点起来的。源头是 Gathin23/cleanyourtv:10-17 建库,作者那条推文 860 万浏览,TechCrunch 10-19 写了一篇《人们在用 AI 把智能电视变笨》。到 11-06,这个仓库 52,550 星、6,705 fork。

TV Detox captured two things. The first was timing: it came only 8 hours later, with an identical story about "my parents' old TV" (whether he had seen the original post before posting can't be confirmed). The second was the video: cleanyourtv required cloning the repo, installing the JDK and Android SDK, and compiling it yourself. TV Detox just needed a pasted prompt, since the APK was already built, and the video walked through the whole process with the before-and-after cut into chapters. When the media wrote about "a trend," they needed a second and third example, and The Verge named him the day he built the repo, and 10-23 wrote another article.

Where users come from

DateTV Detox star (GitHub, same day)What happened
10-189Repo created; YouTube video published; first The Verge piece
10-20338Android Authority, Tom's Guide, Decrypt and others follow up
10-21844Single-day +506, peak
10-231,246Second The Verge piece
11-062,192 / 238 fork+26 that day

The main engine is that video. "Claude Made My Old Android TV Feel Brand New!" has 1,001,971 views by 11-06, 17k likes and 1,130 comments (YouTube, 11-06). His channel had only 4,440 subscribers, and before this his best video got about 12k views. So the recommendation algorithm pushed it to ordinary TV owners; it wasn't carried by longtime fans. The 1M views only brought in just over two thousand stars, for the same reason: most people who watch are not developers who go star repos.

The comments show who is watching. The most-liked one is "Can't wait to see Claude brick someone's TV" (1,012 likes); next come "This is one of the best things I've seen" (860 likes) and "Best use of AI" (436 likes). Some people had real problems: "TV stuck in a reboot loop, my Acer has no volume key and I can't get into recovery mode" (82 likes). Someone also put it bluntly: "You just added AI to Projectivy."

The rest of the traffic came from media. His press list has 18 outlets, in English, German, Spanish, Portuguese, Korean, Hindi and Turkish, and many of the articles centre on cleanyourtv with him mentioned in passing. Then there are discussion threads on r/ClaudeAI and tutorials by other YouTubers. I found no Show HN from him and no sign of star farming.

Beyond stars, what does he want?

The repo homepage link goes not to a website but to his free Skool community "Staffed: Claude Code, AI", with TV Detox listed as the first community project. The first line of the video description is his ebook "Claude Code for Beginners: 27 Real Fixes" (204 pages), the second line is the community; the first selling point on the ebook sales page is "TV Detox video 1M views". I didn't find the ebook price or how many copies sold.

For anyone hoping to get stars, be clear on one thing: the real output of this project is not stars, but a small channel with 4,440 subscribers suddenly having a million-view piece it can use to build a persona. The stars are a side effect.

Who it's competing with

ProjectScale (11-06)How TV Detox differs
Gathin23/cleanyourtv52,550 starsThe source, one day earlier; already has a community model library covering about 300 TVs, plus themes and a phone app
pengchujin/aerial-tv9,951 starsA tvOS-style launcher for domestic TVs like Xiaomi and TCL
simbasjungles/free-my-tv5,917 starsSupports Google TV, LG webOS and Samsung Tizen at the same time
humblemuzzu/dumbtv1,956 starsBuilt only for Fire TV, created the same day as TV Detox
cleanyourtv-app / tellyscope1,665 / 1,539 starsMade as a phone app, no computer needed, no AI needed
tv-home, tv-fresh, Tigris, webos-vibehack and others300–735 starsSame topic, each makes its own brand or style
Projectivy Launcher(Google Play)1.79M installsA long-running ad-free launcher that just doesn't disable preinstalled apps for you

10-17 this category only appeared recently, and within ten days dozens of repos on the same theme popped up. Most of the attention went to cleanyourtv (about 80%+ by stars); TV Detox probably ranks around #4 to #6 among open-source projects on the topic. There is also pushback: PCWorld published "Please don't use AI hacks to debloat your TV."

Is there room left in this wave?

It's past its hottest point. TV Detox's single-day star gains have dropped from a peak of +506 to +26; over the last 7 days it gained 451, versus 7 in the first 495 days; cleanyourtv's stars over the last 7 days are only about a third of its first 7 days (GitHub, 11-06). Mainstream tech media in multiple languages have already covered it, and Android TV, Fire TV, Samsung, LG and domestic TVs have all been done. Another "AI cleans up your TV" repo now won't get media looking for a seventh example.

If it were you

One-line verdict: stop chasing the TV topic; what's worth learning is how it was chased, to apply to the next hot topic.

  • Who it suits: developers with a modest YouTube or X account who can shoot a live demo the same day; or people who want to build their first piece of work for their community or course.
  • Who it doesn't suit: people who only write code and don't make videos. This project got 1M views for 2,192 stars; the stars came mainly from the video, and the repo alone wouldn't have got them.
  • How to do it: pick a topic that is "AI agent + old device, with before-and-after comparison and undo", such as an old router, TV box, car head unit, old Android tablet or printer. Include prompts you can copy directly, prebuilt install packages, undo scripts and a risk note (which models may get stuck on boot, and turn off debug mode when done). TV Detox does all of these, and that's also why it's easier to use than the source.
  • How to get users: when a similar tweet from someone else blows up, follow the same day, use the same story, and pair it with a fuller demo video than the original post, linking the repo, video and tweet to each other. Once media write about it as a "trend", you'll be picked up along the way. Put media badges and a press list at the top of the README.
  • When you need to be early: the window is measured in hours. TV Detox was still able to squeeze into the second tier 8 hours late; repos three days late mostly stalled at a few hundred stars.
  • What signals you misjudged: if, after the next hot topic of this kind appears, the repo and video you publish within 48 hours aren't picked up by any media outlet or big account, it means this approach depends on luck you can't get (algorithm boosts, a journalist naming you). Then stop chasing hot topics and go back to building a tool you maintain long term.

GitHub repo ↗

Research notes: competitor table, acquisition evidence, full research report
Competitors
NameWhereLaunchedScaleHow it differs from this one
Gathin23/cleanyourtv(cleanyour.tv)Open source2026-10-1752,550 stars, 6,705 forks (11-06), author's tweet 8.6M views, 600+ contributors, covering about 300 TVsThe source of the wave, one day before tv-detox; you have to clone the whole repo and compile the launcher yourself with JDK + Android SDK, and it grew into a community model library, themes and a phone app ecosystem. tv-detox only needs you to paste a prompt and download a prebuilt APK, so it's more foolproof, but it's an order of magnitude smaller in scale.
simbasjungles/free-my-tvOpen source2026-10-195,917 starsCovers Google TV, LG webOS and Samsung Tizen at the same time; tv-detox's main repo only does Android TV, with Samsung/LG covered in separate videos.
pengchujin/aerial-tvOpen source2026-10-209,951 starsA tvOS-style launcher for domestic TVs such as Xiaomi and TCL, with Chinese-speaking traffic.
humblemuzzu/dumbtvOpen source2026-10-181,956 starsBuilt only for Fire TV, created the same day as tv-detox with almost identical star count.
man15h/tellyscope / cleanyourtv-appAndroid2026-10-21~221,539 / 1,665 starsCleans up directly over ADB from a phone app, with no computer or coding agent needed, so the entry barrier is lower.
Projectivy LauncherAndroidYears ago1.79M installs on Google Play, +69k in the last 7 days (googleplay library)A mature third-party ad-free TV launcher that doesn't disable preinstalled apps; tv-detox is a one-off AI cleanup plus a built-in minimal launcher.
FLauncher / ATV Launcher ProAndroidYears ago592k / 80k installs (googleplay library)Also a launcher replacement, with no AI and no removal of preinstalled apps.
tutyamxx/androidtv-debloat-script, various ADB debloat gists, XDA tutorialsOpen sourceFrom ¥2021Single digits to a few dozen starsThe old way meant finding package names yourself and typing commands; the AI agent automates "what's on this TV and what can be turned off", which is the key to why this wave broke out.
Google TV apps-only mode (Apps only mode)Big-company features2021Built into all Google TV devicesThe official toggles can turn off recommendations, but they don't speed things up or stop background services, and they don't apply to many older Android TVs.
Where users come from
  • Verified Riding a viral X topic (follow-on posts): Gathin's "Vibe coded my parents' TV" tweet went out at 2026-10-17 08:51 UTC with 8.6M views (Cybernews); Ansub's same-topic tweet "my parents' old Android TV was full of bloatware…" went out at 10-17 17:08 UTC (converted from the tweet ID), 8 hours later, and even the "parents' TV" story is the same; the replies link GitHub and YouTube.
  • Verified Author's YouTube demo video: "Claude Made My Old Android TV Feel Brand New!" was published at 10-18 16:03 UTC with 1M views; the channel's previous top video was about 12k views, with 4,440 total subscribers (YouTube Data API); README and description link to each other.
  • Verified Tech media coverage: The Verge wrote a separate piece on Ansub on the day the repo was created (10-18), and wrote again on 10-23; 10-19~22 Mashable, Android Authority, Tom's Guide, Yahoo Tech, Decrypt, FlatpanelsHD and German/Spanish/Portuguese/Korean/Hindi/Turkish outlets (press.md); the single-day star peak of 10-21 +506 fell right in this stretch.
  • Verified Reddit / secondary creators: several r/ClaudeAI threads cite tv-detox (such as a TCL Beyond TV thread and a Samsung thread); other YouTubers (such as TabsheerTech) made TV Detox tutorials; Instagram has Reels that set TV Detox and CleanMyTV side by side.
  • Inferred HN: on HN there are only scattered low-score posts and critical comments about cleanyourtv, and no Show HN from tv-detox itself.

Ansub/tv-detox: why it took off

Research date 2026-11-06. Data sources: our github / googleplay libraries (agent-im server), GitHub API, YouTube Data API, Jina search and page text, HN Algolia.

Bottom line

tv-detox didn't start this "use AI to remove ads from smart TVs" wave; it is the follower in the second tier that got off to the fastest start. Gathin's tweet "Vibe coded my parents' TV" went out at 2026-10-17 08:51 UTC (8.6M views); 8 hours later Ansub posted a tweet with the same story, created the repo the next day, and the same day published a 4-minute live demo video. The video reached 1M views, and The Verge named him in a report on the day the repo was created. GitHub stars were a by-product (2,192 stars, against 1/24 for the source, cleanyourtv); the author's real goal was to funnel YouTube viewers into his free Skool community and then sell a Gumroad ebook.

What it is

  • A prompt for users to paste into Claude Code / Codex, plus a minimal Android TV launcher written in Java, latest version v1.5.7.
  • The process goes like this: the TV enables developer mode and USB debugging; the AI connects over Wi‑Fi ADB and sorts every app into three groups: "can disable / TV needs it / you're using it"; it asks the user before each step, only uses pm disable to disable (never delete), and keeps an undo list and undo.sh; then it installs a home screen showing only apps, HDMI inputs and the clock; finally it turns off animations, reboots to check, and reminds the user to turn off debugging.
  • The top of the README has "As seen on" media badges and a Skool community button, and the repo homepage link points to the author's Skool community Staffed.

Growth data

Datetv-detox starscleanyourtv starsEvent
10-17—Repo created 08:12 UTCGathin tweet 08:51 UTC; Ansub tweet 17:08 UTC
10-189—Repo created 06:42 UTC; YouTube published 16:03 UTC; first The Verge piece
10-19241,259Mashable, t3n; TechCrunch wrote about Gathin
10-203384,091Android Authority, Tom's Guide, Decrypt, and others
10-21844 (506 peak)10,248Yahoo Tech
10-231,24622,907Second The Verge piece
11-062,192 / 238 fork52,550daily gains fell to +26

Data comes from the GitHub repo_day table (filled in historically for days before 10-28 via deeply). Over the last 7 days it gained 451 stars; over the first 7 days it gained 495. Growth is clearly below the peak.

YouTube data (Data API, 11-06):

  • Main video, "Claude Made My Old Android TV Feel Brand New!": 1,001,971 views, 17,410 likes, 1,130 comments.
  • Sequel (Samsung / LG / Fire TV versions, 10-23): 39,529 views.
  • The channel only had 4,440 total subscribers; before this video, its top single video was around 12,226 views. This is a classic algorithm-amplified hit, not something carried by an existing audience.

Where users come from (growth levers)

  1. Riding the hot topic on X. Gathin's tweet (x.com/gathint/status/2111379569030939102) described removing ads from his parents' Xiaomi TV and swapping in an Apple TV-style home screen, and got 8.6M views (cited by Cybernews). Ansub's tweet (x.com/justansub/status/2111504666861379644, which converts from the tweet ID to 10-17 17:08 UTC) used nearly the same "my parents' old Android TV" story, with GitHub and YouTube links in the replies. The two posts were only 8 hours apart. Whether he saw Gathin's tweet is unverified, but the timing and narrative overlap closely.
  2. YouTube demo video (the main engine). 4 minutes long, with chaptered before-and-after comparisons. The first line of the description links an ebook, the second links a Skool community, followed by the sequel and GitHub. 1M views against 2,192 stars shows the main audience was ordinary TV users, not developers who star repos.
  3. Media wave. press.md lists 18 outlets: English ones include The Verge (10-18, 10-23), Mashable, Android Authority, Tom's Guide, Yahoo Tech, Decrypt, and FlatpanelsHD; German ones include GIGA, Notebookcheck, and t3n; Spanish includes Computer Hoy; Portuguese includes Estadão/TecMundo; Korean includes AI Times and Wikitree; Hindi includes Navbharat Times; Turkish includes LOG. The star peak (10-20 to 10-22) falls right in this coverage window. Many articles actually center cleanyourtv and mention tv-detox as "another example" in passing, such as Cybernews and PCWorld.
  4. Reddit and creators. r/ClaudeAI has several threads, such as "Old TCL Beyond TV was super slow, so I tried this open-source debloat." Other YouTubers (like TabsheerTech) made TV Detox tutorials, and Instagram has Reels pairing TV Detox with CleanMyTV.
  5. HN: No Show HN for tv-detox turned up, only a few low-scoring cleanyourtv posts and criticism along the lines of "pasting a long prompt to clean up a TV is too much hassle."
  6. No evidence of paid acquisition or star buying. The fork/star ratio is 11%, which is normal.

Where the money comes from

Open source and free (MIT); monetization runs through the author's personal brand:

  • Skool community "Staffed: Claude Code, AI": free, positioned as a library of AI "staff" projects you can copy, with TV Detox ranked first. The author says he was product and frontend lead at 3 AI startups and is co-founder of the design studio Supafast.
  • Gumroad ebook "Claude Code for Beginners: 27 Real Fixes": a 204-page PDF. The first selling point on the sales page is "TV Detox video, 1M views." Price and sales were not found.

Competitors and same-topic projects

NameWhereLaunchedScaleHow it differs from tv-detox
Gathin23/cleanyourtv(cleanyour.tv)Open source10-1752,550 stars, 6,705 forks, 600+ contributors, about 300 TV modelsThe source of the wave, a day earlier; requires cloning the repo and building locally with the JDK and Android SDK; already has a mature ecosystem of model libraries, themes, and a community app
pengchujin/aerial-tvOpen source10-209,951 starsA tvOS-style home screen for Chinese TVs (Xiaomi, TCL)
simbasjungles/free-my-tvOpen source10-195,917 starsSupports Google TV, webOS, and Tizen at the same time
humblemuzzu/dumbtvOpen source10-181,956 starsFocused only on Fire TV
udhaykumarbala/cleanyourtv-app, man15h/tellyscopeAn Android phone app10-21~221,665 / 1,539 starsNo computer and no AI agent needed
mihirgupta0900/tv-home, wangrongding/tv-fresh, lesnolie/Tigris, tv-vibehack, webos-vibehack, and othersOpen source10-18~26300–735 starsSame topic, each building its own brand or style
Projectivy LauncherGoogle PlayYears1.79M installs, +7k in the last 69 daysA mature ad-free home screen that avoids preinstalled apps
FLauncher / ATV Launcher ProGoogle PlayYears592k / 80k installsSame as above
ADB debloat scripts and XDA guidesOpen source / forumsFrom ¥2021Single or double-digit starsRequires manually looking up package names; AI automates figuring out what the TV has and what can be turned off
Google TV "apps-only mode"Big-company features2021Built into the systemOnly recommends removals and does not speed anything up; older Android TVs don't have this feature

Bottom line: This is not an empty market. The category of "AI agent cleans up TV over ADB" was born the day 10-17 appeared; within 10 days, dozens of same-topic repos showed up, and cleanyourtv took about 85% of the attention. Among open-source same-topic projects, tv-detox ranks roughly 4rd to 6th.

Differentiation, and whether it's a manufactured ranking

  • Compared with cleanyourtv, tv-detox differs in these ways:
    • Lighter: one prompt plus a prebuilt APK, no SDK needed;
    • Shipped with a real-device video from day one;
    • Beginner-friendly tone: confirms each step, judges OLED screensavers, and ends by reminding users to turn off debugging so devices on the LAN can't be controlled by others;
    • Samsung / LG / Fire TV users get a separate video.
  • These differences only put it in the second tier of same-topic projects; they didn't overtake the source. Its rise was driven mainly by timing (catching a topic someone else had ignited) and distribution (an algorithm-boosted video, plus The Verge naming it the day the repo was built). Product differences were secondary.

How many people know about it

Already widely discussed. Major tech outlets in several languages have covered it; the README and ebook page openly tout "1M views" and media backing, and the category is already crowded with copycats. PCWorld even published "Please don't use AI hacks to debloat your TV" as a counterpoint. No public revenue figures. The novelty has passed its peak: tv-detox's daily gains dropped from +506 to +26, and cleanyourtv's star gains over the last 7 days were only a third of the first 7 days.

Takeaways

  1. The window for riding a hot post is a few hours. As soon as someone else's tweet took off, others followed with the same narrative, a more complete demo video, and a copyable prompt repo. When media write about "a trend," they need a second and third example, and followers get carried along.
  2. Topic formula: "AI agent plus old device or appliance, ad removal and speedup," with selling points of before-and-after results and reversibility. It transfers easily to routers, old laptops, car infotainment, TV boxes, and printers.
  3. Funnel: an open-source repo as bait, monetized through YouTube → free community → ebook. A single hit video can establish the product pitch for a small channel (4,440 subscribers).
  4. Social proof: media badges and press.md placed at the top of the README.

Unknowns

  • Skool member count, ebook price, and sales were not found.
  • Whether Ansub saw Gathin's tweet before posting is unverified.
  • The view count for Ansub's tweet itself was not retrieved (it is not in the x-radar local corpus).
  • How much of this traffic converted into ebook revenue is unknown.

Sources

This article was written by AI from public data and the data we collect daily. Numbers are sourced, and inferences are labeled.