These indicators are portfolio-showcase mock analytics. They are designed to model how a future weekly summarization system could convert cached gaming and AI news into executive-ready market signals.
85/100
+11 pts
Industry Heat compresses the average impact score across the current intelligence feed into a 0-100 market temperature.
Average of all article Industry Impact Scores, rounded to the nearest whole number.
70+ suggests an unusually active news cycle. 85+ means several stories could affect strategy, budgets, hiring, or platform positioning.
87/100
+18 pts
AI Disruption Index isolates AI-tagged and AI-sector stories, then measures their average strategic impact.
Average impact score for articles categorized as AI or tagged with an AI-related affected sector.
A high score means AI is not just present in the feed; it is attached to stories with credible production, labor, platform, or cost implications.
15
15 tracked
Trending Articles counts stories that are either strategically important or accelerating quickly enough to deserve executive attention.
Count of articles with an impact score of 80+ or a trend score of 30%+.
This is a workload signal. If it jumps, the feed has more items worth reading during the weekly brief review.
+43%
+6% 7d
Market Momentum estimates how quickly the tracked themes are gaining attention compared with the baseline feed.
Average of all article Trend Scores, expressed as percentage growth.
Higher momentum favors fast-moving narratives such as platform shifts, AI tooling launches, layoffs, and creator-market spikes.
LoreEngine separates story importance from story velocity. Impact scores answer whether a brief could matter to studios, investors, creators, platforms, or technical leaders. Trend scores answer whether that theme appears to be gaining attention quickly enough to change planning priority.
In production, these scores should be generated once per week on the server, saved to a database or JSON cache, and read by the frontend. They should never be recalculated by browser users or regenerated on every page load.