No. SleekView Feedback reads directly from whatever table or post type EWWW is using, including ewwwio_images and the attachment meta keys EWWW populates. You point it at the source, pick the columns for votes, status, category, author, and title, and the board renders. No ETL job, no sync, no duplicated data.

Yes. SleekView ships with anonymous voting backed by cookies, so public visitors can upvote images and presets without an account. You can also require login if you want the board restricted to designers or paying members, and the same view handles both modes with a single toggle.

Each visitor gets a cookie scoped vote token per item. Logged in users are tracked by user ID. The plugin also exposes a rate limit so a single IP cannot spam the board, which is enough to keep public boards honest without forcing a signup wall in front of designers.

Yes. SleekView accepts a WHERE clause when you wire up the data source, so you can scope the board to JPEG runs, PNG runs, runs from a particular bulk job ID, or any combination of fields EWWW already stores. Different boards on different pages can use different filters.

The Bug category is just a value on the row. You can write it into a meta key EWWW already understands or a dedicated column. Either way it shows up in the WordPress admin alongside the original attachment, so the developer tuning the preset can see the flag without leaving WordPress or opening a ticket.

They write back to the source column, which means EWWW and any of your own queries can sort future bulk jobs, retries, and conversions by that score. Several teams use the score to gate which presets get more files, which makes the board operational and not just a vanity dashboard for the homepage.

Both. SleekView ships as a Gutenberg block, an Elementor widget, a Bricks element, and a classic shortcode. Theme developers can also call the render function from PHP and pass a configuration array, so you can mount the board on any template without touching the page editor.

The view paginates server side and only loads the rows it needs to render the current page. Indexed columns stay fast even on long tables. For really big libraries, scoping the board by upload date or campaign keeps both the query and the audience focused, so the page feels snappy even at scale.