摆烂程序媛 engagement report
@wanerfu - 121K followers on X
Measured over 22 original posts from a 30-day window, last computed on October 5, 2026.
Engagement
A typical post picks up 104 interactions against 121K followers, an engagement rate of 0.087%. Measured over 22 original posts, its engagement rate beats 51% of 20,444 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 18K times each, and 0.589% of those impressions turn into an interaction. That is about 14.6% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.5 posts a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 01:00 UTC, and Sunday is the busiest day of the week. Of the 22 posts sampled, 27% carry an image or video, 23% are part of a thread and 14% link out. The account's strongest tracked post pulled 4.6K interactions, about 45x its own typical post. Recurring topics include #agentictrading, #financialai, #minaraai.
Measured over 22 original posts from a 30-day window, last computed on October 5, 2026. Recurring tags: #agentictrading, #financialai, #minaraai.
Compared with accounts its own size
摆烂程序媛's engagement rate beats 51% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 8 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.
On engagement per impression rather than per follower it beats 28% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.
Where this sits in the catalog
At 0.087%, 摆烂程序媛 sits above the 25th percentile of the 204,798 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.143%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.678% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built
Posting timing
This account posts most often around 01:00 UTC, and Sunday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 27% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 14% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | no effect | -2% to -1% | 42K |
- 27% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 14% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
- Its average post runs 244 characters, which falls in the 180 - 280 characters band. Across the catalog, posts of 180 to 280 characters match the same accounts' other posts almost exactly.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- Sep 29, 202645x their median
别再跟 ChatGPT 说“帮我做个图” 别再跟 ChatGPT 说“设计一张传单” 别再跟 ChatGPT 说“做张海报” 这样只会得到千篇一律的 AI 设计。 换成下面这 8 个提示词:
- Sep 28, 202630x their median
抽屉里的旧手机先别扔,它完全可以变成一台24小时监控摄像头。 屏幕碎了没关系,用了三四年也不影响。 我只花了2分钟就设置好了,画面清楚、还能远程查看,体验不输专业摄像头。 不用买设备,也不用交订阅费。 具体怎么设置,下面一步步教你:
- Sep 27, 20264.3x their median
谷歌刚放了个没想到的东西。 一份 8 分钟教程,手把手教你搭出自己的第一个人工智能代理。 https://t.co/x7QDnjiI2G
- Oct 2, 20264.0x their median
🚨 紧急提示:ChatGPT有一个叫'语言学习模式'的功能。 可以用它从零开始学任何语言,相当于请一位价值2000美元的私教。 这里有7个提示词来激活这个模式:
- Oct 1, 20263.5x their median
一个男人用了5年iPhone。 下午3点电池就没了。手机口袋里发烫。存储空间总是'快满了'。通知不停。相册app卡顿。 他的朋友——前Apple软件工程师——一个晚上坐下来,15分钟内改了10个设置。 电池用到午夜。手机停止过热。释放了40GB存储。通知基本无声,除了重要的。 他说:'感觉像新手机。' 她说:'就是。你用了5年出厂设置。Apple发布的版本是收集最多数据、显示最多通知的——不是尊重你电池和时间的版本。' 这是她改的全部内容 🧵
- Sep 24, 20263.0x their median
Jev 每 2 秒自动买卖,帮我赚了 3,000u+ 4 天近 20 亿美元涌进比特币, 我拿 1 万美元本金, 按一套规则跑了一遍, 扣掉手续费,账上多了 3,120 美元 Jev 负责快判断, Minara 负责翻证据来验证 🔗 https://t.co/3RxIP5iJy0 我是这么跑的👇 #MinaraAI #FinancialAI #AgenticTrading
- Oct 3, 20262.5x their median
别再怪 ChatGPT 回答质量差了。 输出差,是因为提示词写得烂。 这里有 9 个提示词框架,帮你拿到专家级结果: [ 🔖 收藏这条帖子,升级你的提示词 ] 1. R-A-C-E ➣ Role(角色):设定 ChatGPT 要扮演的角色(编辑、教练等)。 ➣ Action(行动):描述 ChatGPT 要执行的任务或动作。 ➣ Context(背景):补充关键背景信息,让意图更清楚。 ➣ Expectation(期望):说明你想要的结果或输出。 2. R-I-S-E ➣ Role(角色):设定 ChatGPT 要扮演的角色或人设。 ➣ Identify(识别):点出主要问题或挑战。 ➣ Steps(步骤):列出达成目标所需的行动。 ➣ Expectation(期望):描述最终输出应该是什么样。 3. S-T-A-R ➣ Situation(情境):描述背景或场景。 ➣ Task(任务):说明涉及的目标或挑战。 ➣ Action(行动):分享采取了哪些步骤。 ➣ Result(结果):说明这些行动带来的结果。 4. S-O-A-P ➣ Subject(主题):描述主要对象或问题。 ➣ Objective(目标):说明这次互动的目的。 ➣ Action(行动):解释将采取哪些步骤。 ➣ Plan(计划):给出解决方案或计划。 5. C-L-E-A-R ➣ Context(背景):提供任务的简要背景。 ➣ Learn(学习):明确需要学习或理解什么。 ➣ Evaluate(评估):定义如何衡量进展或结果。 ➣ Action(行动):列出完成任务所需的步骤。 ➣ Review(回顾):总结结果或关键要点。 6. P-A-S-T-O-R ➣ Problem(问题):说明需要解决的问题。 ➣ Amplify(放大):强调这个问题为什么重要。 ➣ Story(故事):给一个简短的例子或案例。 ➣ Transformation(转变):展示解决方案带来的变化。 ➣ Offer(提议):分享你提出的解决方案。 ➣ Response(回应):建议下一步行动。 7. F-A-B ➣ Features(特点):列出产品或想法的关键特点。 ➣ Advantages(优势):解释这些特点能帮你做什么。 ➣ Benefits(收益):展示它们如何创造真正的价值或结果。 8. 5-W-1-H ➣ Who(谁):确定涉及或受影响的人。 ➣ What(什么):定义主要问题或挑战。 ➣ When(何时):提到相关的时间范围。 ➣ Where(何地):指出地点或背景。 ➣ Why(为什么):解释为什么重要。 ➣ How(如何):描述如何解决。 9. G-R-O-W ➣ Goal(目标):设定你想达成的目标。 ➣ Reality(现状):描述当前的挑战或情况。 ➣ Options(选项):列出可能的行动或前进路径。 ➣ Will(意愿):确定下一步并承诺去做。
- Sep 26, 20261.6x their median
用 ChatGPT 时只会说“想一想”“总结一下”, 真的太浪费了。 其实只要在指令最后多加一句话, 回答质量就能明显提升。 下面这 30 个短语,工作副业都能用,直接复制就行👇
- Oct 2, 2026
GPT-6 Astra 做加密货币研究强得离谱。 我跑这些提示词,感觉就像口袋里装了 24/7 的研究量化团队。 🧵:10 个 GPT-6 Astra 加密研究提示词(可直接复制粘贴)。👇
- Sep 25, 2026
不是你的 ChatGPT 不行,是你的提示词不行。 ❌“帮我写点有创意的” ❌“给我点建议” ❌“帮我看看这个” 三个模糊的请求,三个泛泛的回答。天天如此。 改变这一切的 8 个提示词:
Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.
Recurring topics
The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.
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Reading these numbers
A typical post picks up 104 interactions against 121K followers, an engagement rate of 0.087%. Measured over 22 original posts, its engagement rate beats 51% of 20,444 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 18K times each, and 0.589% of those impressions turn into an interaction. That is about 14.6% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.5 posts a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 01:00 UTC, and Sunday is the busiest day of the week. Of the 22 posts sampled, 27% carry an image or video, 23% are part of a thread and 14% link out. The account's strongest tracked post pulled 4.6K interactions, about 45x its own typical post. Recurring topics include #agentictrading, #financialai, #minaraai.
- What is 摆烂程序媛's engagement rate on X?
- 摆烂程序媛 (@wanerfu) has an engagement rate of 0.087%, based on the median interactions across 22 original posts from the last 30 days against 121,071 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.087%, 摆烂程序媛 sits above the 25th percentile of the 204,798 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
- Does @wanerfu have real engagement?
- Its engagement rate beats 51% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
- When does @wanerfu post?
- Most posts go out around 01:00 UTC, and Sunday is its busiest day, at roughly 2.53 posts per day across the measured window.