AI video's real failure is not quality, it is that the character's jacket changes between shots. Reel Studio makes that a first-class workflow — takes are reviewed against consistency verdicts, the failing ones produce a fix prompt automatically, and you promote the take that passed. Combined with named cast and location bindings written into the shot prompt, that is a genuine answer to continuity rather than a hope that the seed holds. Check credits with get_workspace_status before a batch; generation jobs are where the money goes.
Reel Studio's endpoint covers AI filmmaking end to end rather than exposing a generate call. Films hold scenes, scenes hold shots, and cast and locations are named entities that shots bind to.
- Structure — films, scenes, shots, cast and locations, each with list, create and update tools
- Binding — a shot description references cast and locations by name, so the same character stays the same character
- Generation — a model catalogue spanning image, text-to-video, image-to-video, video-to-video, avatar, lipsync, speech, sound effects and music, with jobs you poll
- Consistency — review_takes reads the model's verdicts across a shot's history and recommends the best passing take; promote_take makes it active; generate_fix_prompt turns a flagged issue into a fix prompt
- Timeline — add, edit, reorder and move visual clips, plus voiceover, effects and music cues with per-lane mute and volume
- Export — start a render and poll for the final video URL
OAuth 2.1 with PKCE, or a personal access token. get_workspace_status reports the authenticated user, the selected workspace and available credits before you spend any. Work is private by default; custom access controls are handled by email.
Paste a URL, then authorize — add the endpoint to your client, then approve the OAuth consent screen