Automation benchmark and evaluation index
Buyers comparing Automation options rely on anecdotes. A maintained benchmark with methodology becomes the citation standard — and a lead engine.
Opportunity score
67
confidence 64%
Related stars · 7d
+18.1k
4 tracked repos · est.
Trend runway
31mo
estimated demand lifespan
Avg breakout odds
67%
7-day cohort probability
Score anatomy
Every factor, its weight and its normalized value — the score is the weighted sum, nothing else.
Demand trajectory — 90 days
+18.1k stars · 7dAggregate star velocity and momentum across the 4 repositories underlying this opportunity · estimated
Underlying repositories
The projects whose trajectories generate this opportunity.
| Repository | Score | Stars · 7d | Stage | ||
|---|---|---|---|---|---|
| langgenius/dify157.3k stars · TypeScript | 77 | 78Healthy | +1.8k | Breakout | |
| Panniantong/Agent-Reach85.7k stars · Python | 76 | 69Healthy | +11.6k | Breakout | |
| JCodesMore/ai-website-cloner-template35.3k stars · TypeScript | 76 | 80Healthy | +4.3k | Breakout | |
| puppeteer/puppeteer95.6k stars · TypeScript | 74 | 83Strong | +411 | Saturated |
90-day execution plan
Days 0–30
Ship the wedge
Build the smallest sellable slice of the data product and put it in front of teams already using langgenius/dify.
Days 30–60
Prove willingness to pay
Convert the Automation community's attention (demand 75/100) into 3–5 design partners at founding-customer pricing under a sponsorship motion.
Days 60–90
Systematize distribution
Publish benchmark/comparison content targeting the topic's search demand and integrate into the ecosystems of the related repositories — the channel compounds while the trend has an estimated 31 months of runway.