refactor: clean up onboarding scroll, props, and magic values

[devin-ai-integration]

refactor: clean up onboarding scroll, props, and magic values

Summary

Refactors the onboarding improvements from #4153 to reduce fragility and hardcoding while keeping the same UX behavior:

• Self-contained scroll: Moved scroll-to-active-step logic from the parent (TabContentOnboarding) into OnboardingSection itself. Each section now owns a useRef and scrolls itself into view when it becomes active. This eliminates the scrollRef + querySelector('[data-step="..."]') pattern and the stepId / data-step coupling between parent and child.
• Named constants: Extracted SCROLL_DELAY_MS (350) and DEFAULT_ICON_SIZE (14) to replace magic numbers.
• BeforeLogin cleanup: Removed the unused onContinue prop (was aliased to _onContinue and never used). Renamed triggered → autoSignInCompleted for clarity.
• Icon size default: Social icon entries use a shared DEFAULT_ICON_SIZE instead of repeating size: 14 on each item; only overrides where needed (X icon at 10).

Review & Testing Checklist for Human

• Scroll behavior on step transitions: The scroll logic now lives inside OnboardingSection and fires via useEffect when isActive becomes true. Verify that smooth scrolling still works correctly when advancing/going back through steps — especially the transition from "upcoming" (component returns null, no DOM) to "active" (component renders, ref attaches, effect fires after render with 350ms delay).
• Hook ordering before early return in OnboardingSection: useRef and useEffect are called before the if (!status || status === "upcoming") return null guard. This is required by React's rules of hooks but worth confirming there are no edge-case issues on mount/unmount cycles.
• Icon size ...rest spread pattern in final.tsx: The "size" in rest ? rest.size : DEFAULT_ICON_SIZE approach works with as const but is slightly unconventional — confirm it reads well and TypeScript is happy with it in CI.

Notes

• Requested by @yujonglee
• Link to Devin run

[devin-ai-integration]

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