Nothing to hand? Load the
— an SVG loader in a custom webpack() block, a --webpack dev
script, a Babel config, swcMinify, a 300 kB route and a published
NEXT_PUBLIC_ secret — or the
,
where the correct verdict is turbopack-ready and the useful output is what to do next.
Paste the build surface — the prescan is free
No upload, no AI: the prescan reads your files in the browser and lists what it mechanically found. It parses the next build route table into real first-load weights and draws them, then lists the flags — a custom webpack() block, a Babel config, a dev script forcing --webpack, a script wiping .next, a pre-16 next pin, removed options (swcMinify, experimental.turbo, next-transpile-modules), routes and shared chunks over the weight thresholds, params/cookies() read without await, barrel imports, "use client" on a page or layout, secret-looking NEXT_PUBLIC_ names and raw <img> tags. Each group explains why it matters. This part costs nothing and happens while you type.
The AI reviews it — this is the metered part
A senior Next.js build engineer's pass: a build posture with the single most important change named, the inventory with each construct's role, prioritized findings across compatibility, dev speed, bundle size, correctness, caching and hygiene — each with the problem, what it actually costs in seconds or kilobytes, the fix and a corrected fragment — and then the ordered plan to get there. Every prescan flag is confirmed or explicitly set aside. Findings may only cite files, scripts, routes and dependencies that appear in what you pasted. Pricing is honest: a worst-case amount is reserved before the run and only what the run actually uses is charged — the meter next to the button shows both.
Fix, export, re-run
The plan as a commented shell script, every corrected fragment in one paste-ready block, the findings as GitHub PR review comments with ```suggestion fences, a tickable action checklist for the ticket, the findings table as CSV, and Markdown or JSON export of the whole review. Then start fixing: tick each finding off on the card as you go, and the prescan re-runs as you edit. The strip above the run button counts the flags you have cleared, the ones still open and any you have just introduced — and when you paste a fresh next build output it names the kilobytes that actually moved, per route and on the shared floor, so you can see “shared floor −48.7 kB, /dashboard −164 kB” before deciding a second review is worth paying for. All of that is in the browser, for free. Reviews are saved to your SkillSafe account when you are signed in, so they follow you to another machine; restore puts the files back in the form too, and Compare with this diffs any two past reviews into what is gone, what is still there and what is new — matched by what each finding is about, since ids are assigned per run.
Derived from the @affaan-m/nextjs-turbopack skill.