Blur and block cyberbullying tweets on Twitter/X before you post or scroll past them
This is our editors' assessment out of 5, not an average of user ratings. The viewpoints on this page are written by AI from what we know about the product. They are not customer reviews.
According to OpenAITools.app telemetry verified on 2026-11-11, yBully (chromewebstore.google.com) is an AI platform indexed under AI Detector generating 0 monthly visits with a month-over-month traffic delta of +0 (0.0%). Its primary geographic market is Global (— traffic share), and it operates on a Free pricing model. Top competing alternatives by monthly volume include Tweeteasy (4.35K visits/mo), Devi AI (35.39K visits/mo), Twitter Personality (4.25K visits/mo).
Blurs toxic tweets nicely. Makes X much more chill.
Catches most hateful comments in my timeline.
False positives happen on edgy jokes.
Good safety tool.
AI-synthesized perspectives grounded in live site inspection, pricing structure, and category benchmarks — presented as editorial viewpoints rather than individual customer testimonials.
Every tweet that loads on Twitter/X is run through a machine-learning classifier that flags cyberbullying content across all pages.
Tweets judged to be bullying are blurred or covered with a label so you can skip them instead of reading them by accident.
Draft tweets are checked before publishing, and the extension restricts you from sending content classified as bullying.
Incorrectly predicted tweets can be reported, and the reports are fed back to improve the model over time.
Earn a trust score as your reported tweets are approved, then use it to contribute training data directly, and review statistics on what was detected.
yBully is a browser extension built to make Twitter/X a less hostile place. Once installed, it watches the tweets that load in your timeline, applies a machine-learning text classifier to each one, and marks anything that looks like cyberbullying. Flagged tweets are blurred or labelled so you can decide whether to view them, rather than being hit by them unexpectedly.
The extension also works on the posting side. Before you publish a tweet, yBully checks the draft against the same classifier and discourages or blocks you from sending content that reads as bullying. When the model gets it wrong you can report the tweet; those reports feed back into retraining, and a trust-score system lets reliable reporters contribute more directly to the dataset used for the next model update. The extension additionally keeps simple statistics about what it has caught for you.
The project remains a small, free, single-purpose tool. Its Chrome Web Store listing shows a modest user base, English-only interface, and no paid tier.
Automatically blur or label bullying replies and tweets so scrolling stays readable without muting whole accounts.
Catch drafts that could read as aggressive or hurtful before they go out from a brand or client account.
Use yBully's labels as a quick screening pass when reviewing reports about harassment.
Report misclassifications and, with a high trust score, help supply retraining examples for harmful-content models.
Side-by-side telemetry comparison of competing AI tools in the same primary category
| Rank | AI Tool | Monthly Visits | MoM Growth | Direct traffic share | Pricing | Head-to-Head |
|---|---|---|---|---|---|---|
| ● | yBully | 0 | — | — | Free | Current |
| 1 | Tweeteasy | 4.35K | +23% | 39% direct | Freemium | vs Tweeteasy |
| 2 | Devi AI | 35.39K | -31.4% | 63% direct | Free Trial, Paid | vs Devi AI |
| 3 | Twitter Personality | 4.25K | -6.6% | 40% direct | Freemium, Free | vs Twitter Personality |
| 4 | No Porn | 629 | -75.5% | 40% direct | Paid | vs No Porn |
| 5 | Qsafe (C9Lab) | 28.08K | +242.1% | 39% direct | Contact for Pricing | vs Qsafe (C9Lab) |
| 6 | ReplyPulse | 69 | 0% | 42% direct | Free Trial, Paid | vs ReplyPulse |
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