Score low-quality risk, not “AI guilt”
The extension reads visible feed text in the browser. It scores low-signal patterns such as generic phrasing, engagement bait, vague authority, repeated structures, thin external links, and comment duplication.
Reddit-first Chrome extension concept
AI Slop Blocker is a browser extension concept for people who want Reddit, X, and LinkedIn feeds with less repetitive AI slop, bot-like replies, SEO spam, and engagement bait. It does not label author identity. It scores low-quality risk, explains why a post was folded, and lets you reveal it with one click.
User research
Join the private research list and pick the feeds you want cleaned up first. Your email is sent through a server-side endpoint only — not stored in browser localStorage or exposed in static files.
Direct answer
AI Slop Blocker is a feed-quality blocker for low-quality risk, not an AI-authorship detector. It looks for combinations of weak signals: template openings, generic advice, engagement bait, dense cliches, missing specifics, promotional links, and repeated comment patterns.
The important distinction: a single signal should not trigger action. A dash, a bullet list, or a polished tone is not enough. The blocker should fold only when several low-signal patterns appear together and no strong human signal offsets them.
How it works
The extension reads visible feed text in the browser. It scores low-signal patterns such as generic phrasing, engagement bait, vague authority, repeated structures, thin external links, and comment duplication.
Specific numbers, dates, prices, version numbers, code, logs, screenshot details, firsthand experience, sourced claims, clear disagreement, and subreddit-specific context all lower the risk score.
The MVP should badge low-risk items and fold medium-risk items. Hidden-by-default behavior is reserved for high-risk patterns later, and the recommended first version keeps folded posts one click away.
AI Slop Blocker should never label a post as “AI.” It labels risk: likely low-signal, repetitive, promotional, or engagement-bait content.
Keyword mutes miss disguised slop and hide useful AI discussions. Combined signals make false positives easier to handle.
Reddit slop, X slop, and LinkedIn slop do not look the same. Each platform needs its own scorer and thresholds.
AI slop is not simply “content made with AI.” Useful summaries, code explanations, translations, and drafts can still help people. The problem is low-quality feed noise: posts that look polished but add no evidence, no lived detail, no specific answer, and no reason to trust the author.
AI Slop Blocker is being designed for people who open Reddit to find human signal and instead hit recycled growth hooks, vague expert claims, bot-like replies, and thin link drops. The first version focuses on Reddit because users can validate the filter quickly in real communities; later versions can use separate scorers for X and LinkedIn.
Each folded item should offer two simple actions: Not slop and Hide more like this. Those choices should be saved locally to tune your own thresholds and rules, not used to build a public shame list or upload your feed by default.
The right metric is not “AI detection accuracy.” The right question is whether folded posts are usually low-value. Before launch, AI Slop Blocker should test 300-500 real samples labeled slop, borderline, and not slop, then optimize for high precision first. Missing some slop is acceptable; folding useful posts is the real product failure.
No. It does not promise to prove whether text was generated by AI. It scores low-quality risk from combined signals and describes the reason: for example, Score: 78, Reasons: generic phrasing / engagement bait / low specificity.
The planned MVP is local-first. Visible feed text is scored in the browser by default, with no feed upload required.
Reddit first, because low-quality risk is easiest to validate where subreddit context, comments, and moderation norms are visible. X and LinkedIn should use separate scorers after the Reddit blocker is useful.