先说结论

People who mostly use chat-style AI and are trying to keep up with new tools make the same mistake over and over: they treat every new project like search. That gets expensive fast.

You see an update, almost scroll past, then stop because you are worried this might be the one thing that changes what you should pay attention to next. Use the wrong filter and you burn time, budget, and attention on noise. The hidden cost is worse: you keep orbiting surface hype and miss the one change that should affect your next move.

That is why mvanhorn / last30days-skill is interesting. It is not really search. It is closer to a vote compiler: it compiles upvotes, likes, and market odds into a ranking of what people actually care about.

为什么这次值得看

The README makes the bet explicit: rank people signal before editor signal, with upvotes, likes, and real-money signals feeding the sort. The changelog says the same thing in product form. Version 3.4.0 on 2026-06-18 added crowd-vote weighting. Version 3.10.0 on 2026-07-04 rewrote how Top Community Comments are ranked across platforms.

That is the tell. When the ranking logic keeps changing, the ranking logic is the product logic.

关键证据

A tool update is worth reading only if it changes your next decision, not because it shipped a longer feature list.

My boundary here: this read is based on the public README and changelog through v3.10.0 on 2026-07-04, not on a benchmark or truth test. High reaction is not the same as high truth.

So the practical move is simple: use last30days-skill as a first-pass attention filter, not as the final answer. Then add your own filter before you trust it. If you know someone drowning in AI tool news, share this with them.

#AIResearch #DeveloperTools #OpenSourceAI #SignalVsNoise

适合谁 / 下一步怎么用

最后落到动作：share