Docs / source reviewed
ASO Workbench
Use Jev signals in App Store keyword research
How this project uses Jev
- Input
- Keywords, country and language, app description, and public search signals
- Jev decides
- Brand terms, search intent, app fit, and demand tier
- Code executes
- Code ranks opportunities alongside available Apple Ads data; official values take priority over estimates
Evidence and limitations
Jev is called through OpenRouter and needs a user key. Estimated demand is not official Apple search volume. Author-reported correlation and error were not reproduced here.
This project has not been run independently here. Author-reported results are not independently verified results.
Original sources
- https://github.com/mustafakendiguzel/aso-workbench/blob/037bfb68b7c6c9dc7f844ee63704c46a0277b65c/README.md ↗
- https://github.com/mustafakendiguzel/aso-workbench/blob/037bfb68b7c6c9dc7f844ee63704c46a0277b65c/Sources/ASOProviders/OpenRouter/JevClient.swift ↗
- https://github.com/mustafakendiguzel/aso-workbench/blob/037bfb68b7c6c9dc7f844ee63704c46a0277b65c/Sources/ASOWorkbench/Services/ResearchService.swift ↗
- https://github.com/mustafakendiguzel/aso-workbench/blob/037bfb68b7c6c9dc7f844ee63704c46a0277b65c/Sources/ASOWorkbench/Services/IdeaFinder.swift ↗
- https://x.com/mustafakndgzl/status/2102471894167433625 ↗