Yes. Store the video URL as a column and inject it via selector mapping into a video block. YouTube, Vimeo, and self-hosted MP4 all work. For YouTube, wrap the URL into an iframe embed in the template so the source can stay clean as just the watch URL.

Store style as a column (style: hardstyle, sport, both) and selector-map a style badge. A second URL pattern under /kettlebell/style/{slug}/ generates style index pages. For exercises that appear in both with different cues, add style-specific cue arrays and let the template render whichever style the page targets.

Yes. Build separate page groups for programs and complexes (rows with title, lifts in order, rep targets) and link from each program to the relevant exercise pages. Both groups read coordinated sources so adding a lift makes it available to programs that reference it.

Yes. Each generated URL is added to the SleekRank sitemap. The base template is excluded and noindexed. Submit the sitemap in Search Console and new exercises get crawled within hours of cache flush. Exercise-name queries rank well because the structured per-page content signals authority.

Cache duration is configurable per source. For active development, set fifteen to thirty minutes. For a stable library, a day or longer is fine. A manual flush via wp-cli makes urgent updates appear immediately on the next request.

No. The base template is a normal WordPress page. Any theme with clear typography and callouts works. Level, focus, and implement badges render through the theme's existing styles plus the few classes you assign. SleekRank only injects values; the visual identity stays in the theme.

Store a typical_weights column with men and women columns or a JSON object (typical_weights: {men: 24kg, women: 16kg}). Selector mapping renders the typical weights alongside sets/reps. This is reference language, not prescription, and the column makes it easy to update across the library at once.

Yes. Add an equivalents array with slugs from a barbell or dumbbell library when a kettlebell move parallels a loaded movement. List mapping renders the equivalents as linked items, helping athletes who train across implements navigate without leaving the site.