Paste a Douyin, Xiaohongshu or Bilibili profile link to fetch the profile and the latest 30 posts (publish time, caption, length, views / likes / comments / saves / shares). Code works out posting frequency, posting-time distribution, engagement rate, top posts and a recent-half-vs-earlier-half growth or decline signal, then a diagnosis (where it stands, content pillars, what works, problems, concrete next steps) is saved as a note with the key numbers attached. Pick the data source from the start node's drop-down: the built-in browser (nothing to set up and free; Xiaohongshu / Douyin need a signed-in browser profile, other platforms work too, and the numbers are the page's rounded ones) or TikHub (needs the plugin and an API key; 2 calls per run, from about $0.001 each — see your TikHub bill; complete fields, steadier, no sign-in). Plus one or two AI chat calls (one more on the browser route to read the page).
Turn a topic into a creative brief, script and visual bible; characters and locations already in the asset library are reused with their references, and only new ones get a turnaround sheet or concept art — saved to the library — auto-build a 3D blockout with each shot's camera position and move, then generate each shot from a first frame (and a last frame where needed) painted on the blockout — or straight from the turnarounds and the blockout camera move — and assemble, caption and export the video. Cost: by default up to 8 shots, each one video generation plus one or two keyframe images, on top of up to 7 turnaround and location images (none for those already in the library), 5 chat calls and per-shot narration — the most expensive template here; max_shots on the start node caps the shot count, and shot_seconds sets each shot's length (preset to the length the chosen video model can make that is closest to its default).
Remove background hiss, transcribe the video with timestamps, identify pauses, fillers and repetition, then create a cut plan and a cleaned video while preserving the original. Suited to talks and interviews up to about 30 minutes; split longer footage first.
Transcribe a video sentence by sentence, translate each line, lay translated subtitles on the original timecodes, then dub each line and time-compress it back into its own slot. Pick the target language on the translate step (English by default). The original voice is separated out and the background music kept; a voice separation engine must be ready before the workflow starts.
