"It keeps running SHA-256": a small plugin that fixes GPT-5.6's quirks, gets 3600 stars through a forum help post
What it is A brake for AI coding agents like Codex and Claude Code: a set of rules plus an interception layer that blocks unwanted SHA-256 checks, unrequested refactors, file edits during read-only reviews, and repeated verification loops.
Why it took off After GPT-5.6 launched, Codex users were collectively frustrated by its "computing SHA-256 everywhere"; the project opened with that specific symptom and a funny meme name, got repeatedly recommended in linux.do help threads, and was picked up by reposts and plugin directories.
BHow you could follow it Stop building generic anti-over-engineering skills. Watch for the specific flaw everyone complains about after a new model release, build a small tool that counters it within a month, put the model and the symptom in the name, and recommend it in forum help threads.
- Data (updated daily) · Repo created 2026-08-11 · 3,710 stars · 7 days +272
GitHub · stars Data 2026-08-29 → 2026-11-08 (72 days, 31 observations). Points before 10-28 come from deeply / archive backfill, not every day has one
In 2026 Sep 3, someone on linux.do posted complaining that GPT-5.6 writes code too defensively; the post was soon seen by 973 people. Three fixes were recommended in the thread, one being lennney/stop-that-shit on GitHub, which translates to "stop making up history". The repo was only created in Aug 11, its author had just 3 repos on GitHub and no reputation at all. 87 days later it had 3657 stars. It hasn't beaten anyone in its broad category: the leading project in the same area is 50 times its size. Its stars came from a very narrow spot: a newly released model showed a flaw everyone recognized, and it was built specifically to fix that flaw. Below I cover what it is, where the stars came from, and which parts you can learn from if you want a project that gets stars the same way.
A forum help post
The original poster wrote:
Recently I've noticed GPT really likes to anticipate all kinds of problems it might run into, then write a pile of safety checks against them, so the code keeps getting bloated... smoke tests, and it keeps running SHA-256.
The third reply said: "I see people on X complaining about this everywhere." The fourth said: "It's clearly written in AGENTS.md and it still doesn't work, it's still defensive programming."
This flaw has a backstory. GPT-5.6 Sol launched in Jul 9, and within days r/codex had "GPT 5.6 uses sha256 everywhere" and "Is GPT-5.6-Sol a hash fetishist?", and an OpenAI community post suggested renaming it "5.6 Sol off the rails". Almost everyone who writes code with Codex has seen it: you ask it to export a file, and it quietly writes a checksum that nobody reads.
By September, on linux.do, where heavy Chinese Codex users gather, this had become a recurring type of post. The person who recommended stop-that-shit in that thread just wrote one line: "This seems to work well."
What it is
A "brake" for AI coding agents, installable into six tools including Codex, Claude Code, and OpenCode. It has two layers:
- A Skill (rules): tells the model what to finish and what to stop. The author calls the behaviors to stop SHIT, with each of the four letters covering one category: S scope creep (fixing one spot and refactoring neighboring modules), H useless defensiveness (checksums nobody reads, compatibility layers for an imagined future), I intent overreach (told to do a read-only review, yet the files still get modified), T task looping (re-running what was already tested and reviewed).
- A Guard (interception): uses each tool's Hook to stop actions before they run, such as unrequested hash operations, file writes in read-only mode, sub-agents over budget, and file writes outside an allowlist. When a checksum really is needed, write
hash=allowto permit it.
The README's first line is the scene everyone has seen:
You asked the Agent to export one file, and it quietly computed a SHA-256 nobody reads, saying it was "just in case".
Below is a two-line before-and-after: delete the report.csv.sha256 line, and the file still ships as usual. The next sentence mocks a common workaround: "Every time you get annoyed, you add another rule, and eventually AGENTS.md starts making up history too."
Where the stars came from
The author first posted it around, and it got little response. On Aug 12 he published "Codex started computing SHA-256, and I knew a small task was about to get big" on Juejin (286 reads); on Aug 21 he nominated it in the issue section of Ruan Yifeng's weekly; on Aug 29 he posted a Show HN, getting 3 points and 0 comments. The first wave in the English community didn't take off.
The real traffic came from help posts on linux.do. On Sep 1, "Your GPT isn't listening anymore either?" was posted, and the accepted answer was "medium reasoning effort + ponytail + stop that shit"; the same day someone opened a thread asking "Has anyone here used stop-that-shit?"; Sep 3 was the opening post above. After that, in Oct 3, Oct 13, and early November, each time someone posted a new complaint about GPT, someone in the thread recommended it again (the early-November thread on page three: "Textbook defensive programming, bro, try... stop-that-shit"). Working backward from third-party star-tracking records, about 1700 stars came in during the first 26 days after the repo was created (inferred), most likely during this stretch.
Then reposts and directory sites built up a long tail. 51CTO (9-01), bytenote (9-22, 2.2k stars at the time), several CSDN tutorials, a Telegram channel, and a YouTube "GitHub trending weekly" episode all covered it. On the English side, only @DanKornas on X posted an introduction in Sep 24, plus a reel from an Instagram repost account. It was also listed by more than a dozen skill and plugin directories, and in Oct 27 it made it into "Best Codex Plugins in 2026", described as "stops Codex from doing work you didn't ask for". The author also forked a string of awesome lists, apparently submitting PRs one by one to get listed (inferred).
Daily star counts for the last three weeks (from GitHub daily snapshots, 11-06):
| Date | Cumulative stars | Daily |
|---|---|---|
| 10-16 | 2673 | Twenty to thirty a day |
| 10-22 | 2937 | +150, the highest in the observation window; I didn't determine what drove it |
| 10-28 | 3273 | +80, around the time of "Best Codex Plugins" |
| 11-04 | 3568 | +74 |
| 11-06 | 3657 | +53; +292 in the last 7 days, +428 in the first 7 days |
There are only 76 forks, about 2%. But skills are usually installed from plugin marketplaces and don't need forks, so this ratio isn't unusual. It has 10 external contributors and 62 merged PRs, which shows people are actually using it.
Why this one
A concrete symptom word. "AI over-engineering" is too abstract, and readers don't feel it; "it's computing SHA-256 again" is something every Codex user has seen with their own eyes. STS opens with this from the title, the description, and the first line of the README, so readers recognize their own experience at a glance.
A name that turns into a meme. "Stop That Shit" is a swear, and "别再造史了" ("stop making history") puns on "造屎" (make shit), a nod to the "屎山" (shit mountain, i.e. spaghetti code) meme. It also breaks into the initials S/H/I/T. On linux.do, where the crowd loves its in-jokes, a reply saying "just install stop that shit" is funny and easy to remember by itself.
It landed in the right thread. Most of its recommendations come from help threads, not its own post area. Help threads keep getting new posts, so the project keeps getting recommended.
It looks like a real project. 11 versions, CI, 18 Bad/Good test cases, an evidence file with side-by-side runs (including the runs where nothing changed), and READMEs in Chinese, English and Korean. Directories and lists are willing to take projects like this. But the Hook interception tech isn't the hook for spreading it: nobody on linux.do who recommended it explained how it works, and one person complained they "couldn't find the mechanism I most wanted to know about."
Who else is doing the same thing
"Stop the AI from over-engineering and editing code outside its scope" is one of the most crowded skill niches of the past 2026 year (GitHub stars, 11-06):
| Project | What it is | Scale | Compared with alternatives |
|---|---|---|---|
| multica-ai/andrej-karpathy-skills | A general coding guideline riding Karpathy's name | 230K stars | General, pure prompt |
| DietrichGebert/ponytail | A "laziest senior engineer" persona skill | 185k stars, +5130 in the last 7 days | General, model-agnostic; linux.do often recommends the two together |
| JuliusBrussee/caveman | Makes the agent cut the fluff and save tokens | 118K stars | Controls the mouth; STS controls the hands. They complement each other. |
| miqdadbadjuber/anti-slop | Filters the cookie-cutter AI look and copy | 8335 stars | Aesthetics-focused |
| whitelonng/mancode | Anti-over-engineering harness with scoring | 360 stars | English community, not tied to one model |
| linux.do's LEAN-MODE-SKILL | Skill from a forum post | Not verified | Also targets GPT's over-validation, 18 days later |
It's the small one in this niche (3.7k vs 185k). The winner for general "anti-over-engineering" was already decided, so STS got a narrow spot: GPT-5.6's hash and defensive habits, in the Chinese community. I haven't seen any repo copy its name or code yet.
Its weak spot is here too. After GPT-6 launched in Sep 22, a Taiwanese outlet wrote that "now that models are stronger, Skill files should be cleaned out." In late September to early October, it gained only 7 to 20 stars a day. It later went back to dozens a day, and in early November people on linux.do were still complaining about GPT, so the pain point hasn't fully gone away.
If it were you
Verdict: Don't build another "anti-over-engineering" skill; this space is packed. What's worth copying is its approach: watch for a specific flaw a new model introduces that the community is collectively complaining about, then ship a small tool that fixes it right away. This approach doesn't depend on fame, since the author was a new account; but it usually tops out at a few thousand stars, and the window follows the model version.
Who it's for: Heavy users of Codex, Claude Code and Cursor who already hang out on linux.do, r/codex, r/ClaudeAI and similar forums, and who can spot "everyone is complaining about the same thing" within one or two weeks of a new model launch.
Who it's not for: People who want to build a long-term, general-purpose dev tool; people who won't track model versions or spend time replying in forum threads.
How to do it: Find the next symptom phrase. Within two weeks of a new model launch, search these forums for "again", "always", "sick of it". Look for a flaw you can explain in one sentence, that people recognize from a screenshot, and ideally one that editing AGENTS.md doesn't fix. Put the model name and symptom right in the tool name and description; show a before-and-after code block of two or three lines on the first screen of the README; include a test suite and side-by-side runs so directories can list it. Give it a Chinese name that works as a forum-reply meme.
How to get users: Don't rely on launch posts; rely on help threads. Subscribe to the relevant keywords on the forums, reply to every "how to fix X" post (from your own account, and say you built it), and show how your tool handles the scenario in the original post. At the same time, submit the repo to skill and plugin directories and awesome lists, and write a comparison piece like "X vs adding rules to AGENTS.md" for Juejin and CSDN. You can post on Show HN, but don't expect much.
When to move: The first month after a new model launches. STS built its repo 33 days after GPT-5.6 launched, so it missed the early complaint period. Whoever ships first for the next model claims the spot.
Signs you've misread it: A week after posting, nobody in the forum help threads is recommending you; or the vendor fixes this flaw in a minor release; or the "symptom" you picked takes three sentences to explain before people understand it.
Research notes: competitor table, acquisition evidence, full research report
- Competitors
Name Where Launched Scale How it differs from this one DietrichGebert/ponytail Open source 2026-06-12 185,138 stars, 7 days +5,130; HN 98 points A general "lazy senior engineer" prompt, model-agnostic, no interception. STS targets GPT/Codex hashing and defensive coding, with Hook interception. linux.do often recommends the two side by side. multica-ai/andrej-karpathy-skills Open source 2026-01-27 229,830 star A CLAUDE.md general guideline riding Karpathy's fame. STS is a narrow, specific symptom tool that adds an execution-layer Guard. JuliusBrussee/caveman Open source 2026-04-04 117,723 star Cuts output tokens (controls the mouth). STS controls actions (controls the hands). They complement each other. miqdadbadjuber/anti-slop Open source 2026-08-07 8,335 star Filters generic AI UI, text and code. Aesthetics-focused, doesn't handle task boundaries. FerroxLabs/agents-md Open source 2026-04-19 733 star An AGENTS.md prompt that stops drive-by refactors. STS has Hook interception and task modes. whitelonng/mancode Open source 2026-06-27 360 star An anti-over-engineering harness with scoring. English community, not tied to a specific model symptom. LEAN-MODE-SKILL (linux.do post) Other 2026-08-29 Forum post, unverified Also constrains GPT over-validation and swallowed errors. Pure skill, 18 days after STS. AGENTS.md / CLAUDE.md, plus the built-in hooks in Codex and Claude Code Big-company features Already around All users Users have to write the rules themselves. STS packs the rules and interception together. The README opens by mocking "AGENTS.md is starting to make history itself." - Where users come from
- Verified Platform event: GPT-5.6 Sol's hash / over-defensive flaws: GPT-5.6 07-09 launched; r/codex "GPT 5.6 uses sha256 everywhere", OpenAI community "5.6 SOL drift edition" (07-12); STS's description states "for Codex/GPT" and "stop unrequested hashes"
- Verified Organic recommendations in linux.do help threads: 09-01 "Your GPT isn't listening either?" had an accepted answer that included STS; 09-03 "GPT5.6 defensive programming gone too far" got 973 views, and STS was one of 3 solutions; 10-03 and 10-13, plus the early-November posts, were still recommending it
- Verified Author self-submissions: Juejin 08-12 (286 reads), self-nomination issue #11298 for Ruan Yifeng's weekly (08-21), Show HN 08-29 (3 points), lennney.com product page and comparison piece
- Verified Chinese reposts / SEO content: 51CTO 09-01, bytenote 09-22 (at 2.2k stars), several CSDN posts, Telegram 鑫源AI sharing, YouTube GitHub trending weekly #5
- Verified English repost accounts: X @DanKornas 09-24 introduced it in a post; Instagram github_dev reel
- Verified Skill / plugin directories and awesome lists: skills.sh, TypingMind, QAI, skillsdirectory, the hol.org registry and "Best Codex Plugins 2026" (10-27), awesome-codex-plugins and others; the author forked several awesome lists, likely to submit PRs
- Inferred Source of the star surge from 10-21 to 10-23: trendshift shows +143/+67/+71, but I couldn't find a matching post or repost
Why lennney/stop-that-shit (Stop That Shit / 别再造史了) took off
Channel: GitHub · Research date 2026-11-06 · Data card: 2026-08-11,87 days since the repo was created, 3657 stars (live GitHub API count that day: 3686), 76 forks, +7 in the last 292 days, +7 in the first 428 days, peak single-day gain in the observation window +150 (10-22)
Bottom line
GPT-5.6 Sol (launched 2026-07-09) had an obvious, easy-to-describe flaw in Codex: it computed unused SHA-256 hashes everywhere, was over-defensive, and scope crept. Chinese heavy Codex users (linux.do, Juejin) were fed up with this, and the project took a ready-made meme name (Stop That Shit / 别再造史了, where "造史" puns on "造屎") and a concrete "SHA-256" example, and packaged the complaint into something you could install. The stars mostly came from users voluntarily recommending it in help threads like "how to fix GPT over-engineering", plus the author's own submissions to Juejin, Ruan Yifeng's weekly and Show HN, and rounds of reposts from dozens of skill directories and overseas repost accounts. This is a pain-point repo riding a platform event; it's not based on product innovation, and it has no resource backing.
1. First, the competitors: who else does the same thing
"Stop AI coding agents from over-engineering and editing code outside their scope" was one of the most crowded skill niches of the 2026 year. The top players are two orders of magnitude bigger:
| Name | Form | Launched | Scale (GitHub repo_profile, 2026-11-06) | How it differs from STS |
|---|---|---|---|---|
| multica-ai/andrej-karpathy-skills | Open source, one CLAUDE.md | 2026-01-27 | 229,830 stars, 7 days +3,483 | A general coding guideline riding Karpathy's name (with "surgical changes" and "simplicity first"). Pure prompt, no interception. |
| DietrichGebert/ponytail | Open source skill (+ ponytail.dev) | 2026-06-12 | 185,138 stars, +5,130 in 7 days; HN 6-14 98 points, 9-07 33 points | The "laziest senior engineer" persona, also anti-over-engineering. Pure prompt, model-agnostic. linux.do users often recommend it alongside STS ("mid-tier reasoning + ponytail + stop that shit, three-pronged"). |
| JuliusBrussee/caveman | Open source skill + proxy | 2026-04-04 | 117,723 star | Controls the "mouth" (cuts output tokens); STS controls the "hands" (actions). bytenote's original piece said the two complement each other. |
| miqdadbadjuber/anti-slop | Open-source rules | 2026-08-07 | 8,335 star | Filters generic AI UI / text / code, aesthetics-focused |
| peteromallet/desloppify | Open source harness | 2026-02-11 | 4,080 star | Fix the slop code after the fact, not block it up front |
| FerroxLabs/agents-md | Open-sourced AGENTS.md | 2026-04-19 | 733 star | "Act like a senior engineer, not an intern": stops drive-by refactors, prompt-only |
| whitelonng/mancode | Open source harness | 2026-06-27 | 360 star | "Stop your AI from over-engineering", scored across five modes |
| linux.do LEAN-MODE-SKILL | Skill from a forum post | 2026-08-29 | Forum post, scale unverified | Targets the same GPT quirks like over-validation and swallowed errors, 18 days after STS |
| dev-flow.top | Add-ons | Around 2026-09 | Self-promoted in a linux.do post, scale unverified | Also targets GPT-5.6 defensive programming |
| Big vendors ship this capability | AGENTS.md / CLAUDE.md, Codex /hooks, Claude Code hooks | Already around | — | Users write the rules themselves; the STS README opens by mocking this approach ("AGENTS.md itself has started writing history") |
Bottom line: lots of competitors, big players at the top. STS is a small account in this space (3.7k vs 185k / 230k). It didn't win the big fight against over-engineering. Instead it became the default answer in a much narrower niche: GPT-5.6 / Codex hash and defensive-programming quirks + the Chinese community.
2. Growth levers: where users come from
In chronological order:
- Author's own posts (verified)
- 2026-08-11 repo created. 08-12 the author posted on Juejin under the handle "pause here": "Codex started computing SHA-256 at first, and I knew a small task was about to get big again" (286 reads), juejin.cn/post/7672719051587076105
- 08-21 submitted to Ruan Yifeng's "Tech Enthusiast Weekly" under the title "[Open-source self-promo] Stop That Shit: you only want a result, why does AI still generate SHA-256?", github.com/ruanyf/weekly/issues/11298 (0 comments; I couldn't confirm whether the weekly included it)
- 08-29 posted to Show HN, only got 3 points and 0 comments (hackernews library). The first English wave didn't take off.
- The author's own site lennney.com published a product page and a comparison article, "Stop That Shit vs AGENTS.md" (08-30)
- Organic recommendations in linux.do help threads (main channel, verified)
- 09-01 "Your GPT isn't listening anymore either?": the accepted answer was "medium reasoning effort + ponytail + stop that shit" (307 views) linux.do/t/topic/2842570
- 09-01 "Anyone using stop-that-shit? How does it work in practice?": "it was built for scenarios like 5.6 sol where it overbuilds easily", 6 likes (from search snippet)
- 09-03 "How are the bros solving GPT5.6's over-defensive coding?": 973 views, 17 replies. STS is one of the 3 solutions. OP's words: "keeps running SHA-256 on everything"; another replier says "X is full of people posting about this" linux.do/t/topic/2849618
- 10-03 "GPT's efficiency sometimes really makes me despair", 10-13 "Folks, any way to avoid GPT over-engineering?", and an early-November "I'm really sick of GPT…" page 3 ("Textbook defensive programming, try… stop-that-shit"). Every new GPT-complaint thread re-recommended it.
- The fastest star growth came in this phase: from 08-11 to 09-06, roughly 1,676 stars (trendshift shows a net gain of 2,010 from 09-07 to 11-06, back-calculated from the totals), and on 09-07 alone it was still +62
- Chinese secondary coverage / SEO content (confirmed): 51 CTO's "Adding a brake to AI coding agents" (09-01), a bytenote introduction post (09-22, 2.2k stars at the time), several CSDN posts (09-21 a tutorial on running Codex via TaoToken, 10-03 a "how to submit a Bad Case" post by a GitCode mirror account), the Telegram channel "鑫源AI分享", and a YouTube video, "GitHub Trending Weekly #5".
- English reposter accounts (confirmed): the big X account @DanKornas posted "Your agent was asked to export a file. It also wrote a checksum nobody uses…" 09-24x.com/DanKornas/status/2102929505765523916; the Instagram reposter github_dev put it out as a reel; and people mentioned it in a LinkedIn post too. Who drove the 10-21 (+143), 10-22 (+67), and 10-23 (+71) waves is not confirmed, could be a reposter account or a newsletter.
- Skill / plugin directories and leaderboards (long-tail SEO, verified): skills.sh, TypingMind, QAI, skillsdirectory (Grade A), proskills.md, skillleaderboard, aiskill.market, the hol.org plugin registry. hol.org's "Best Codex Plugins in 2026" (10-27) reads "Scope guard that stops Codex from doing work you didn't ask for". Also hashgraph-online/awesome-codex-plugins, awesome-dsh-plugin, the RepoFOMO leaderboard, and codexworkshop.com (08-30 listing). The author also forked a string of awesome lists (awesome-codex-plugins, awesome-claude-skills, awesome-mcp-servers, visible on their GitHub account), which looks like an effort to seed listings with PRs (inference).
- Platform events (verified): after GPT-5.6 Sol 07-09 launched, r/codex threads ("GPT 5.6 uses sha256 everywhere", "Is GPT-5.6-Sol a hash fetishist?") and an OpenAI community thread ("5.6 SOL should be renamed 5.6 SOL drift edition", 07-12) all complained about the same quirk. The STS intro directly says it targets "Codex/GPT scenarios" and "stop unrequested hashes", and EVIDENCE.md uses 471 runs of gpt-5.6-sol as a control, effectively pinning the project to this event. After GPT-6 Sol / Luna 09-22 launched, a Taiwanese outlet ran a piece saying "now that models are stronger, Skill files should be cleaned out", which is a potential headwind for STS. Daily gains did fall into single digits from late 09 to early October (10-02 to 10-11 per day, 7–20).
- No evidence found for: paid promotion, star farming (fork rate is about 2%, low, but skills are usually installed through plugin markets rather than forked, so not necessarily anomalous; 10 contributors have submitted real PRs and 62 were merged, which suggests real users), Xiaohongshu / TikTok, or celebrity endorsements. Searches of the local x-radar X corpus for "stop-that-shit" and "stop writing history" each returned 0 results, so no discussion formed on X.
3. Why it took off
- The pain point was manufactured by a platform event, and there's a specific "symptom word": GPT-5.6 Sol likes computing SHA-256, a quirk every Codex user has seen and can recognize at a glance (r/codex, the OpenAI community, and several linux.do threads all discuss it). STS doesn't talk about "over-engineering" as an abstract idea. It opens with "exporting a file, and it quietly computed a SHA-256 nobody reads", directly matching the reader's own experience to the tool.
- The meme name travels well in Chinese: "Stop That Shit / 别再造史了" is both a swear and a pun on "造屎" (making shit), tied to the "屎山" (shit mountain) meme, and it breaks into four S/H/I/T categories (scope creep / useless defense / intent overreach / task looping). In linux.do's "folks" culture, "install stop that shit" is itself a funny, memorable reply.
- Hit the right channel: linux.do is where heavy Chinese Codex users gather. "What to do when GPT won't listen" is a recurring post type there, and STS became one of the standard replies to those threads, creating a steady long tail of traffic (it kept getting recommended from September through November).
- Slightly harder than a pure prompt: Guard uses Codex / Claude Code / OpenCode hooks to block hash operations before they execute, write-restrict files in read-only mode, cap subagent budgets, and limit file writes to an allowlist. It also has five task modes (review/answer/monitor/change/watch) and explicit override flags like
hash=allow. For people who find that adding rules to AGENTS.md doesn't help, this is a reasonable step up. - The author is diligent and the project looks credible: 11 releases (0.0.1 → 0.2.5), CI, 18 Bad/Good judgment test cases, an EVIDENCE.md with control tests and the null results, READMEs in Chinese, English, and Korean, and coverage of six hosts (Codex, Claude Code, OpenCode, Hermes, Pi, Oh My Pi). When directory sites list it and writers cite it, it looks like a serious project rather than a one-off prompt.
4. Differentiation, and whether that's why it broke out
Compared with pure-prompt "be a lazy engineer" tools like ponytail and karpathy-skills, STS differs in three ways:
- It targets one model's specific symptoms (GPT-5.6 / Codex hash and defensive-programming quirks), not generic guidelines.
- It intercepts at execution (Hook Guard), not just advises.
- Chinese-first, with a meme name.
Why it took off: points 1 and 3 explain it; point 2 mostly doesn't. What brought in stars was the positioning "this is the cure for 5.6 sol's quirk", plus a funny name. The recommendations on linux.do were almost all "this feels like it works" or "matches what I read in the intro". Nobody discussed the technical details of hook interception, and some people complained they "couldn't find the mechanism I most wanted to understand". Hook interception added credibility and got it into "Best Codex Plugins"-style lists, but it wasn't the spread driver. At scale it never challenged ponytail (185k), which suggests the winner was already decided in the general "anti over-engineering" mindset. STS settled into second tier within its niche.
5. How many people can see it
- It spreads within small circles: the Chinese Codex community (several linux.do threads, Juejin, CSDN, the 51CTO post, bytenote) and skill directory sites. In English, there's only @DanKornas's post and Instagram reposts. Show HN got 3 points, and the X corpus has no discussion. There's no revenue to speak of (MIT open source, no paid tier).
- Copycats / similar projects: linux.do's LEAN-MODE-SKILL (08-29, which also constrains GPT's "over-validation"), dev-flow.top, and mancode are doing similar things. I didn't find any library that directly copied its code or name.
- Momentum: +292 over the last 7 days, less than the +428 from the prior 7 days, but 11-03 still shows +76 and 11-05 shows +50, so the long tail is still going. How long it lasts depends on whether new GPT models keep having this quirk.
6. What to borrow
- Find a specific symptom the community collectively complains about after a model launch (the symptom word should be as specific as "SHA-256"), then build a small tool that targets it. Name it and describe it with the symptom and model name, riding the search and help-seeking traffic the platform event creates.
- Being recommended where users ask for help works better than spamming launch channels: linux.do keeps producing "how to fix GPT over-engineering" help threads, and the accepted answer in those threads is the best distribution you can get.
- A meme name + an abbreviation philosophy (S/H/I/T) makes "recommending it" itself a fun thing to say.
- Package it with evidence: Bad/Good cases, controlled runs, multi-host support. That makes it easy for directories and leaderboards to list.
- The downside also comes along: it's tied to one model's quirks. If the model changes (GPT-6), demand may weaken with it.
7. Still unclear
- Day-by-day sources for the roughly 1,700 stars from 08-11 to 09-06: the GitHub stargazer timestamp API returns 404 for this repo, so the early curve isn't available and I had to reconstruct it from trendshift. I didn't check whether the author posted an "open source promo" on linux.do.
- Unclear who drove the +143 / +67 / +71 jumps between 10-21 and 10-23.
- Actual install count: no plugin marketplace install numbers (skills.sh and similar pages didn't return figures).
- Whether Ruan Yifeng's weekly newsletter featured it.
- After the GPT-6 series launched, does the "over-defensiveness" pain point still exist? (Someone on linux.do was still complaining about GPT in early November, so it hasn't gone away.)
Sources
- GitHub API: repos/lennney/stop-that-shit (stars, releases, contributors), users/lennney
- Our database: github.repo_profile (competitor star counts, 2026-11-06), hackernews.story (Show HN 08-29 3 points; ponytail HN 06-14 98 points)
- trendshift.io/repositories/155928 (daily star gains, 09-07 to 11-06)
- juejin.cn/post/7672719051587076105 ;github.com/ruanyf/weekly/issues/11298
- linux.do/t/topic/2842570 ;linux.do/t/topic/2849618 ;linux.do/t/topic/2981035 ;linux.do/t/topic/3018291 ;linux.do/t/topic/3109676 ;linux.do/t/topic/2830055(LEAN-MODE-SKILL)
- www.bytenote.net/article/stop-that-shit-agent-guard ;www.51cto.com/article/854445.html ;blog.csdn.net/weixin_42356162/article/details/166237945
- x.com/DanKornas/status/2102929505765523916 ;www.instagram.com/reel/DeYmD9qyjG_/
- hol.org/blog/best-codex-plugins-2026 ;github.com/hashgraph-online/awesome-codex-plugins
- GPT-5.6 launch: en.wikipedia.org/wiki/GPT-5.6; the hash complaints: www.reddit.com/r/codex/comments/1v0bpv2/gpt_56_uses_sha256_e…, www.reddit.com/r/codex/comments/1vn7r57/is_gpt56sol_a_hash_f…, community.openai.com/t/5-6-sol-should-be-renamed-5-6-sol-dri…