A prompt to make GPT cut the fluff, 25 days, 650 stars: a flaw 'everyone is complaining about' is a ready-made topic

A Zhejiang University developer packaged 'GPT is wordy and makes excuses' into a prompt-plus-hook that installs with one command, posted it on LINUX DO, and got over a hundred stars in three days, 25 days and 650 stars in total. The star count is modest, but the playbook is clean: the complaints were already there, the paper was ready, and the before/after image is understood at a glance. Below is what it is, where the stars came from, who's following it, and whether you should build one yourself.

A post published at noon

On 2026 Oct 13 at noon, a post appeared in LINUX DO's Develop section titled 'Open source! Reject defensive programming! Give GPT Astra Sol taste and let it talk like a human!!', by XTer, tagged with the community's 'open source promotion' label. The body was short: a GitHub link, a before/after image (on the left, Codex's default answer, with sentences like 'I'll first confirm…' and 'to be safe…' highlighted; on the right, the answer after installation), one line of explanation ('the system prompt sets the general rules first, then each user message is followed by a few reminders'), and a last line: 'Tuning and PRs welcome, friends.'

Most replies underneath were 'trying this now', 'marking this', 'looks good'. As of 11-06, the post had 6.6k views, 336 likes, and 82 replies (LINUX DO post page, 11-06). Related posts recommended below it had titles like 'GPT over-defensiveness is terrifying, does anyone have ways to cope?', 'Friends, any way to avoid GPT's over-engineering?', and 'GPT 6 Astra review doesn't talk like a human, what do I do?'. The problem this project addresses has long been asked about in the community.

What it is

NB-Corp/gpt-with-taste, with the slogan 'Better judgment. Better taste. Less ceremony.' It isn't a model or an app. It's a 'behavior recipe':

• A system prompt, loaded through Codex's official model_instructions_file entry, so GPT-6.1 Sol / GPT-6 Astra write less defensive hedging, make routine calls on their own, and digest sub-agent results before handing them back to you;
• Three hooks, one each when you submit a message, when a sub-agent starts, and when a sub-agent result comes back, each adding a reminder so the model doesn't slide back to its old habits in long chats;
• Install with node scripts/install.mjs --hooks. It leaves your model, permissions, MCP and AGENTS.md alone, and comes with update checks and restore instructions.

The same English recipe compiles to 6 tools: Codex, Claude Code, Kiki (the author's own agent workbench), Pi, Oh My Pi, and DeepSeek Harness (dsh). The last three were added by community members via PRs.

Why now

The complaints were already there. "GPT writes defensively and talks too much" is already a meme in Chinese developer circles. On X, someone posted a screenshot titled "feel GPT's defensive writing." A Skill aimed only at academic writing, anti-defensive-writing-Skill, already had 5,351 stars on GitHub (11-06). 10-14, Codex retired GPT-5.5 and made GPT-6.1 Sol the default model (reported by dev.to), and a lot of people had just been frustrated by the new model's tone. This project went live the day before.

Backed by a paper. The repo's research.md cites an arXiv paper, "Writing for the Reviewer: Defensive Writing in GPT Models." When GPT-6 Astra was asked to "preemptively answer possible reviewer objections," 33% of its claims were softened by its own edits. AI judges scored these rewrites highly, while human readers found them harder to read. "Rejecting defensive writing" went from a feeling to a citable finding, which gave people something to say when sharing it.

The before/after is clear at a glance. The main body of the LINUX DO post is a highlighted comparison image, and the README and GitHub Pages have full before-and-after pairs.

Easy to install without worry. A repost on Chinese X (@Jolyne_AI, 10-18,775 views) that said "Oh my, Codex can finally talk less nonsense" praised specifically that "the original config is left untouched."

Where the stars came from

GitHub star count: 10-16 on 217,10-22, 423,11-06 on 630 (live API 651, forks 35). In the last 7 days it gained +130, faster than the +7 in the 77 days before that. Early November it was steadily adding 15~32 stars a day. I couldn't find specific sources; my guess is the long tail of reposts and aggregators. It hasn't been on Hacker News, I found no dedicated Reddit thread, and there's no media coverage.

The author side is quiet. The GitHub account NB-Corp has only this one repo and 1 followers, and the main developer X-T-E-R has 66 followers. From 10-12 to 10-17 they made 26 commits in a burst, and the main branch hasn't been updated since 10-17.

Who it's competing with

There are also some direct forks: loLollipop/gpt-with-taste (11-05, self-described as "This fork of") and lzlQWQ/gpt-with-taste-CN (a Chinese localization). Prompt files have no barrier to entry, and agent-purge left it far behind within two weeks.

What it does well and what it doesn't

What it does well: it packages a prompt as something installable, rollback-able, and hook-enabled. One source file compiles to 6 tools, so users of niche tools can submit PRs themselves, and each new tool brings a new batch of users.

But the stars didn't come from those features. Almost no repost mentions hooks or multi-tool support. They all say "less nonsense, better judgment." The growth came from the meme, the image, and the post.

What it doesn't do well: the author stopped updating after 10-17, and it has only 650 stars. That suggests the topic "GPT should talk less nonsense" has a low ceiling. The people who care are mainly heavy Codex users in the Chinese community.

If it were you

Verdict: worth trying. This isn't a spot you need to race for (the GPT-defensive-writing niche already has five or six projects). It's a repeatable star-growth play: every time a new model ships, a batch of new habits everyone complains about shows up.

Who it's for: developers who live in LINUX DO, V2EX, or a tool's Discord and are heavy users themselves; people who can make a before/after image that's clear at a glance; people willing to turn a prompt into a "product" with an install script.

Who it's not for: anyone hoping for thousands or tens of thousands of stars (this category tops out at a few hundred to a thousand or two, unless you catch a big word like taste); anyone trying to build a general "agent persona manager" to compete with agent-purge or codex-keysmith on features; anyone unwilling to keep chasing prompt updates with each model version.

How to do it:

• How to replicate: watch for the next model generation (when Codex, Claude Code, or Gemini CLI change their default model, new complaint threads appear in the community right away), pick a specific habit (over-engineering, adding unnecessary tests, refusing to delete code, editing ten files for one change), and package it as a recipe plus hooks.
• Switch audiences: this one took off through Chinese posts, but the English-speaking version of the same complaint can go to Reddit's r/ChatGPTCoding and r/codex. Conversely, tuning packs that catch on in English are often empty in Chinese.
• Fix what it got wrong: it has no reproducible evaluation. Build a small benchmark with the same set of tasks, measured before and after installation with automatic scoring. That turns the comparison image into a comparison table. gpt-instruct reached tens of thousands of stars through its evaluations.

How to acquire users: first find a vertical community and post by its promotion rules (LINUX DO requires the "open-source promotion" tag, and the README links back to the community). The body of the post is a highlighted comparison image. Citing a paper or a set of numbers helps. For the first three days, reply to every piece of feedback in the thread and merge PRs the same day, then let the YouTube compilation accounts and X repost accounts pick it up on their own.

When to get in early: move with the model generation. Publish within one to two weeks of the new default model launching. If you miss it, wait for the next change rather than chasing an old habit that five or six projects already own.

Signs I'm wrong: (1) within two weeks of the next default-model change in Codex or Claude Code, no concentrated complaint threads appear in the community, which would mean the "tuning pack" topic is fading; (2) the vendor builds a similar behavior switch into the product (for example, a "less talk" option in Codex personality), and new stars for this kind of repo drop together; (3) conversely, general tools like agent-purge keep growing while specific-recipe projects stall, which would mean people want a manager, not another prompt file.

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Data and sources: GitHub API and daily star counts (10-16 to 11-06); LINUX DO post linux.do/t/topic/3016674 (11-06 views, likes); LinkedIn post by Arthi R. 10-15; YouTube video from ManuAGI 10-17; posts from X accounts @Jolyne_AI, @fhwofjow51260, @vintcessun, @bkdgiffug; a dev.to report on the Codex default-model change; the repo's README and docs/research.md. I could not confirm the source of the +10-16 stars on 136, whether the Chinese X reposts were organized by someone, or how NB-Corp relates to the author's own Kiki workbench.