'Move that button a bit further left': how a screenshot annotation tool gained 1,400 stars in 56 days

A solo developer with a single repo built a screenshot tool for telling AI 'change this spot,' self-promoted in Chinese developer communities for a month, and gathered over 600 stars. In Oct 28 it was featured in HelloGitHub's monthly and doubled in a week. The idea isn't new, and English-speaking developers built similar things earlier. Its edge is that 'anything on screen can be annotated,' along with a Chinese cold-start route anyone can follow.

A self-promo post that just said 'pleeease'

Late in 2026 Sep 24, a linux.do user named inginnng posted an 'open-source self-promotion':

While vibe coding... I had to hand-type super long edit instructions, like 'move the button in the top right a bit further left,' 'make this card a bit bigger,' 'the color here is wrong.'

The project is called EditHere ('edit here'). The demo in the post was a small game he made with AI: take a screenshot, click, draw boxes, and write notes on the image, then export a JSON that you paste to the AI, which makes the changes and you take another screenshot to compare. Below the post he added: 'If you find it interesting, please give it a star, pleeease.'

The first serious reply was a cold splash of water: 'This feels a lot like the Agentation MCP idea from half a year ago.' The author's answer later became the project's whole pitch: Agentation can only annotate HTML, 'but many people build exe or Godot games... the pages we see can't be edited component by component the way HTML can,' so he chose to annotate only the screenshot's pixels and let the AI figure out 'what this pixel means.'

The post got 112 likes. Ten days later he posted again from a different angle, titled 'The all-purpose tool for accurately editing AI images, frontend, games, and video,' which named Agentation directly and got 99 likes. In the replies he added a candid line: 'I've been wanting to promote it, but it just doesn't seem to get out there, hhh.'

What it is

A locally run desktop screenshot tool (C++/Qt, with a full Windows release and macOS / Linux previews), plus a single-HTML-file web version. After taking a screenshot or opening an image or video, you can:

• Click-annotate, box-annotate, and add global notes: each note is numbered and tied to pixel coordinates;
• 'Big bang': slice the image into regions it recognizes, then drag and resize components directly, recording their positions before and after. Things like 'move this block over there and make it bigger,' which are hard to express with arrows, can be dragged out directly;
• Frame-by-frame video annotation, OCR, and long screenshots;
• Export JSON with the 'original image + coordinates + layout changes', leaving the original image unmarked.

The cleverest step is how it connects to AI. The repo includes edithere-cli and a skill for Codex / Claude Code: midway through a change, the AI can launch the annotation window itself and pause to wait; you annotate and click 'Done, return to AI,' and it takes your feedback and keeps going. Installation needs no manual work either: the README has a 'Let AI install it for you' section with a prompt you paste to your coding agent, and it installs itself.

It calls no models and charges nothing. The license is PolyForm Noncommercial (a noncommercial license, not MIT, which some reposted articles got wrong).

The curve: a month of self-promotion, and one day of a monthly feature

The two curves tell two different stories. The plateau in mid-to-late October shows that community self-promotion alone would have topped out this tool at around 600 stars. The jump in 10-28 was almost entirely driven by a single HelloGitHub distribution: the v0.12.3 release that went out that day was downloaded 1,403 times (GitHub Releases, 11-06), the most of any version. After the monthly issue, it settled into a steady 30~65 stars a day, which is its natural pace without outside help.

Two more numbers: it shipped 29 versions in two months, almost one every other day; the 29 versions have 5,700 cumulative downloads (including repeat downloads on upgrade, so not 5,700 unique users).

Where the stars came from

All of these were free channels in the Chinese developer community. No ads, no Product Hunt, Hacker News, or Reddit, and I didn't find any recommendations in the English community either:

1. linux.do open-source self-promo, posted twice. The second post wasn't a repeat. It changed the pitch from "give feedback on the frontend" to "annotate AI-generated images, games, and videos too," and sharpened the difference with a one-line comparison: "Agentation only works on HTML." The author replied almost every comment under the post: someone said the Windows shortcut captured the wrong window, and he sent a private message and fixed it the same day; someone asked about OCR, and it shipped in the new version four days later; someone wanted a Linux build, and that got added too.
2. X Chinese repost account. Small reach, about 2,000 views.
3. HelloGitHub monthly. Published on the 28th of each month. Once included, the README can carry a "HelloGitHub Featured" badge. For a small C++ tool, this one channel outweighed the previous month of everything else.
4. Long tail: CSDN tutorials, articles auto-generated by GitCode, and assorted GitHub aggregator sites, sustaining dozens of stars a day.
5. The product itself: a prompt for "let AI install it for you" plus a skill turns the user's coding agent into the entry point for installing and invoking the tool.

The README is also a channel: the first thing on screen is a GIF. The AI starts an annotation, the person writes feedback on the image, clicks "Done and return to AI," and the interface gets fixed. The monthly newsletter and the repost accounts could use it directly.

Who's competing for this

"Handing visual feedback to a coding agent" isn't an empty space, and EditHere isn't the first to try it:

Three things stand out. First, the English-language leaders are all on the "web DOM" route. Snip and Remarc, which handle non-web screens, both stalled under a few hundred stars. The same idea never found the right distribution in the English community. Second, EditHere was the first in the Chinese community to turn this into a working product, and I haven't seen a new repo with the same concept take off since 10-28. Third, big companies already offer page annotation inside their own tools, but only for the web so far. If Codex or Claude's desktop app ever ships built-in "annotate the screenshot and then edit it," a large share of this category's room will get squeezed out (inference).

If it were you

Verdict: worth trying, but be clear about what you're up against. EditHere doesn't prove that "screenshot annotation" is a scarce idea (the English community has plenty of similar tools). What it proves is that a small tool with a concrete pain point, a good demo, and a fit with agents, combined with the path of a linux.do self-promo → repost accounts → HelloGitHub, can reach over a thousand stars in two months. The idea can change; the path can stay the same.

Who it suits: a solo developer who can write a desktop or web tool, uses Codex / Claude Code for their own work every day, has a specific pain point they keep hitting, and can reply to comments one by one in Chinese communities and ship a release every other day.

Who it doesn't suit: anyone who wants to build a Chinese version of EditHere, since it already holds that spot in the Chinese community; anyone who only wants web DOM annotation, since the English leaders sit at five thousand to over twenty thousand stars and big companies are building it too; anyone who will publish the repo and then walk away without replying.

How to do it, three directions, ranked from most to least confident:

1. Change the scenario, keep the method: find the next place where "it's hard to explain to AI" and build an input tool for it. Examples: point out to AI which second of the audio is wrong, circle the rows in a data table that are off, or give feedback on a PPT or design draft. The common thread: the human uses the tool to state the feedback clearly, and the AI works out the meaning. Build it as a CLI plus a skill so the agent can launch your tool on its own.
2. Fix what EditHere left undone: its macOS and Linux builds are still previews, and it hasn't broken into the English community. There's room for a native macOS version, English-first, built specifically to plug into Claude Code and Cursor. But snip and Remarc already tried, and neither took off, so you'd have to do distribution better than they did.
3. Switch ecosystems: build it as a plugin inside the Figma, Godot, or Unity editors and earn stars in that ecosystem's community.

How to get users: follow its path. Put a GIF on the first screen of the repo that explains "before / after" in 15 seconds. The first self-promo post explains the pain point; the second switches the pitch and benchmarks against the leading project in one sentence ("it only does X, I do Y"). Reply to every comment after posting and ship fixes every other day based on feedback. Once you have a few hundred stars and a polished demo, submit to HelloGitHub (issues come out monthly, on the 28th). For the English direction, the equivalents are Show HN, r/ClaudeAI, and r/cursor on Reddit. Add a "let AI install it for you" prompt to the README.

When to move: the sooner the better. For agent input tools, the window depends on when big companies build the feature into their own products. That could happen within six months (inference).

What would mean you got it wrong: ① Codex, Claude Code, or Cursor's desktop app ships with "screenshot annotation + drag layout + send back to agent" built in. Then this whole category becomes a nice-to-have. ② EditHere drops back to single digits a day by late November, and nobody engages with the issues. That would mean the 10-28 spike was the monthly newsletter's doing, not real demand. ③ The reverse: an English version of this kind of tool reaches the Hacker News front page and passes a thousand stars in a week. That means the English-language gap is real, and you should move fast.