Automated Job Filler
Extension

The extension approached job-application automation from inside the browser. Instead of controlling a separate browser session, it explored reading the active page, identifying common form fields, and mapping stored profile information into them.

That apparently simple workflow contains difficult interface and privacy questions. Forms use different labels and markup, sensitive information must be handled carefully, and an incorrect match can be worse than leaving a field empty.

The prototype focused on field detection, value mapping, and assisted completion. A robust version would need layered matching based on labels, names, accessibility attributes, input types, and nearby text rather than a single brittle selector.

The user remains the final authority. The safe interaction model is to suggest or fill visible values, highlight uncertain matches, and never submit without deliberate review. Data minimization and local storage boundaries are also core design requirements.

This was an exploratory prototype, not a production extension. Its repository documents an early attempt to understand extension structure and form automation across several major job sites.

The project complements the Python Job Applier experiment: one investigated data collection and scripted browsing, while this one investigated assistance embedded directly in the user's browser context.

Interface automation fails at the edges, so confidence and graceful fallback matter more than maximizing the number of filled fields.

A future iteration would use an explicit schema, per-site adapters, confidence indicators, encrypted or minimal local storage, and tests built from representative but non-sensitive form fixtures.

• Scope and claims are limited to what the surviving project record supports.
• Future updates will add verified media, measurements, and milestones as they become available.

The public repository preserves the inspectable portion of this project.