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Intermediate
Generated

Build a Login Page with Auth Metrics Tracking

Create a real login page with working authentication and instrument it to capture useful investment-app auth metrics such as signups, login attempts, success rate, failures, and drop-off.

9 steps45 verify checks60-120 minutesWorks with: emergent · chatgpt · claude · cursor
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Context Pack

Paste this first. It briefs the AI on requirements, constraints, and the Definition of Done before your first build prompt.

Context Pack
PROJECT CONTEXT:
The project is an investment-related app that needs a real login page with authentication and metrics tracking. The goal is not just to render a UI, but to implement working auth flows and capture measurable events around user access behavior.

GOAL:
Build a functional login page with real authentication, validation, error handling, and analytics events for key auth metrics so the app owner can measure user behavior around access and conversion.

REQUIREMENTS:
- Create a login page with email and password inputs
- Implement real authentication against the app's auth provider or backend
- Support login success and login failure states
- Validate email format and required password before submission
- Show clear error messages for invalid credentials and network failures
- Track metrics for page view, login attempt, login success, login failure, and logout
- Track failed login reason when possible, such as invalid credentials or network error
- Persist authenticated session so refresh does not immediately log the user out
- Redirect authenticated users to a protected app area after login
- Prevent unauthenticated users from viewing protected pages
- Add a simple metrics view or data output path so tracked events can be confirmed
- Ensure implementation works in the actual app, not only as a mock UI

CONSTRAINTS:
- Use the existing stack in the project instead of replacing it
- Do not fake authentication with local-only UI state unless explicitly labeled as temporary
- Do not claim analytics works unless events are actually sent or stored
- Keep the first version focused on auth metrics, not full product analytics

DEFINITION OF DONE:
- A user can enter valid credentials and access a protected page
- Invalid credentials produce a visible error and a tracked failed-login event
- A successful login produces a tracked success event with timestamp
- Refreshing the app preserves the authenticated session when supported by the auth provider
- Protected routes block unauthenticated access and redirect to login
- Login page view, submit attempt, success, failure, and logout events can be verified in storage, logs, or analytics output
- The implementation is wired to real auth logic and not just visual front-end behavior

COMMON FAILURES TO AVOID:
- Building a login form that looks complete but does not authenticate against a real backend or auth service
- Tracking metrics only in console logs without storing or sending them anywhere testable
- Redirecting after login without actually persisting the authenticated session
- Showing generic success states even when auth requests fail
- Leaving protected routes accessible because route guards were not implemented

Paste this into your AI builder first. It teaches the AI what you want before you give it the build prompt.

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