nitpicks.ai · Workflow & Planning
3 items
Nitpicks allows you to record your application bugs and fixes them automatically. Create recordings of your application bugs and get them fixed on a GitHub pull request. You can also select and annotate UI components individually for specific changes. Supported workflows: ✅ Record your screen explaining the bug or change you want to make, and receive a GitHub pull request with the code changes. ✅ Annotate UI components during QA reviews and get them all addressed automatically in a pull request. ✅ Review the pull request that Nitpicks generates, and the requested changes are also implemented automatically. You never need to touch a line of code manually. ❓ Who can use Nitpicks? Everyone on your team, whether technical or not, can easily use Nitpicks to improve the product, even your customers! It just requires a natural explanation of the bug. We have users who are product managers, designers, engineers, sales reps, support agents, and more. ❓ Do I need to know how to prompt AI for software development? No. There is no need to know prompt engineering or anything about the application, just an explanation of the bug or feature you want to implement. ❓ Which errors can Nitpicks fix? - User-facing errors on your UI, even when those include backend changes or API requests. - Web design fixes - Frontend development and issue fixing - Design QA and UI/UX fixes - Visual bugs - UI styles and CSS fixes such as wrong colors, bad contrast, etc. - Quick design adjustments like margins, paddings, tooltips, title copies, etc.
Oct 10, 2025
rating_count is the Chrome Web Store ratings count, not a written-review count.
Media assets
Screenshots and videos on the listing.
Has promo video
Whether the listing includes at least one video.
Languages
Declared language locales.
Developer website
Listing exposes a developer website URL.
Contact email
Listing exposes a contact email.
Keyword in name
Case-insensitive substring match in the name.
Keyword in description
Case-insensitive substring match in the description.
Keyword occurrences in description
Count of case-insensitive occurrences in the description.
Category user-count percentile
Share of same-category extensions with fewer users (null if unknown).
These are transparent listing completeness / keyword signals, not a prediction of Chrome Web Store search ranking.