McLife-Desk — 忙碌了一天，回到家，你打开麦当劳，却突然纠结：今天吃了什么？这周点了几次？这个月花了多少钱？热量会不会超标？ 于是有了 **McLife Desk 麦门人生工作台**。它记录每一次点麦：日期、餐品、金额与热量，生成专属点餐日历；按当月消费次数和金额解
Tracks individual McDonald's orders, spending, and calories to generate personal dining reports.
Why this scored 0
every term, weightedEngagement gained per hour since the last capture, against the fastest item on its own source
Whether that velocity is itself speeding up, as a per-hour rate
How many independent communities are talking about the same entity
Decays to zero over 14 days
Subtracted once something is big and old — we rank what's next, not what's peaked
Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On a topic's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology
Outlook
low confidence · estimate, not a guarantee7-day
~0
range 0–12
14-day
~0
range 0–14
30-day
~0
range 0–19
Signal history
7-day window (free)projected trajectory (estimate, not a guarantee)
Entities
Embed a live signal badge
[](https://www.signalcrest.app/topic/gh%3A1413837358)
Drop this in a README or blog post — it updates automatically as the score moves.