sora

Creates or manages short video clips for the current project (product demos, marketing spots, cinematic shots, UI mocks). Defaults to sora-2 and a structured prompt augmentation workflow, and prefers the bundled CLI for deterministic runs. Note: $sora is a skill tag in prompts, not a shell command.

• Generate a new video clip from a prompt • Remix an existing video by ID • Poll status, list jobs, or download assets (video/thumbnail/spritesheet) • Batch runs (many prompts or variants)

• If the user has a video id and wants a change → remix • If the user has a video id and wants status or assets → status/poll/download • If the user needs many prompts/assets → create-batch • If the user asks for two versions with a small change (same shot, different subject/detail) → create the base, then remix for the variation • Otherwise → create (or create-and-poll if they need a ready asset in one step)

• Decide intent: create vs remix vs status/download vs batch. • Collect inputs: prompt, model, size, seconds, and any input reference image. • If batch: write a temporary JSONL under tmp/ (one job per line), run once, then delete the JSONL. • Prefer CLI augmentation flags (--use-case, --scene, --camera, etc.) instead of pre-writing a structured prompt. If you already produced a structured prompt file, pass --no-augment to avoid double-wrapping. • Run the bundled CLI (scripts/sora.py) with sensible defaults (see references/cli.md). For long prompts, prefer --prompt-file to avoid shell-escaping issues; pair with --no-augment if the prompt is already structured. • For async jobs, poll until complete (or use create-and-poll). • Download assets (video/thumbnail/spritesheet) and save locally. • Remove intermediate files created during invocation (for example prompt.txt, remix_job.json, temp JSONL). If the sandbox blocks rm, skip cleanup or truncate the files without surfacing an error. • Iterate with a single targeted change per prompt.