sora

name

sora

description

Use when the user asks to generate, edit, extend, poll, list, download, or delete Sora videos, create reusable non-human Sora character references, or run local multi-video queues via the bundled CLI (`scripts/sora.py`); includes requests like: (i) generate AI video, (ii) edit this Sora clip, (iii) extend this video, (iv) create a character reference, (v) download video/thumbnail/spritesheet, and (vi) Sora batch planning; requires `OPENAI_API_KEY` and Sora API access.

Sora Video Generation Skill

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

When to use

• Generate a new video clip from a prompt
• Create a reusable character reference from a short non-human source clip
• Edit an existing generated video with a targeted prompt change
• Extend a completed video with a continuation prompt
• Poll status, list jobs, or download assets (video/thumbnail/spritesheet)
• Run a local multi-job queue now, or plan a true Batch API submission for offline rendering

Decision tree

• If the user has a short non-human reference clip they want to reuse across shots → create-character
• If the user has a completed video and wants the next beat/continuation → extend
• If the user has a completed video and wants a targeted change while preserving the shot → edit
• If the user has a video id and wants status or assets → status, poll, or download
• If the user needs many renders immediately inside Codex → create-batch (local fan-out, not the Batch API)
• If the user needs many renders for offline processing or a studio pipeline → use the official Batch API flow described in references/video-api.md
• Otherwise → create (or create-and-poll if they need a ready asset in one step)

Workflow

1. Decide intent: create vs create-character vs edit vs extend vs status/download vs local queue vs official Batch API.
2. Collect inputs: prompt, model, size, seconds, any image reference, and any character IDs.
3. Prefer CLI augmentation flags (--use-case, --scene, --camera, etc.) instead of hand-writing a long structured prompt. If you already have a structured prompt file, pass --no-augment.
4. Run the bundled CLI (scripts/sora.py) with sensible defaults. For long prompts, prefer --prompt-file to avoid shell-escaping issues.
5. For async jobs, poll until terminal status (or use create-and-poll).
6. Download assets (video/thumbnail/spritesheet) and save them locally before URLs expire.
7. If the user wants continuity across many shots, create character assets first, then reference them in later create calls.
8. If the user wants to iterate on a completed shot, prefer edit; if they want the shot to continue in time, prefer extend.
9. Use one targeted change per iteration.

Authentication

• OPENAI_API_KEY must be set for live API calls.

If the key is missing, give the user these steps:

1. Create an API key in the OpenAI platform UI: https://platform.openai.com/api-keys
2. Set OPENAI_API_KEY as an environment variable in their system.
3. Offer to guide them through setting the environment variable for their OS/shell if needed.

• Never ask the user to paste the full key in chat. Ask them to set it locally and confirm when ready.

Defaults & rules

• Default model: sora-2 (use sora-2-pro for higher fidelity).
• Default size: 1280x720.
• Default seconds: 4 (allowed: "4", "8", "12", "16", "20").
• Always set size and seconds via API params; prose will not change them.
• sora-2-pro is required for 1920x1080 and 1080x1920.
• Use up to two characters per generation.
• Use the OpenAI Python SDK (openai package). If high-level SDK helpers lag the latest Sora guide, use low-level client.post/get/delete inside the official SDK rather than standalone HTTP code.
• Require OPENAI_API_KEY before any live API call.
• If uv cache permissions fail, set UV_CACHE_DIR=/tmp/uv-cache.
• Input reference images must be jpg/png/webp and should match target size.
• JSON input_reference objects use either file_id or image_url; uploaded file paths use multipart.
• Download URLs expire after about 1 hour; copy assets to your own storage.
• Batch-generated videos remain downloadable for up to 24 hours after the batch completes.
• create-batch in scripts/sora.py is a local concurrent queue, not the official Batch API.
• Prefer the bundled CLI and never modify scripts/sora.py unless the user asks.
• Sora can generate audio; if a user requests voiceover/audio, specify it explicitly in the Audio: and Dialogue: lines and keep it short.

API limitations

• Models are limited to sora-2 and sora-2-pro.
• API access to Sora models requires an organization-verified account.
• Duration must be set via the seconds parameter and currently supports 4, 8, 12, 16, and 20.
• Character uploads currently work best with short 2-4 second non-human MP4s in 16:9 or 9:16, at 720p-1080p.
• Extensions can add up to 20 seconds each, up to six times per source video, for a maximum total length of 120 seconds.
• Extensions currently do not support characters or image references.
• This skill supports editing existing generated videos by ID.
• The official Batch API currently supports POST /v1/videos only, with JSON bodies rather than multipart uploads.
• Output sizes are limited by model (see references/video-api.md for the supported sizes).
• Video creation is async; you must poll for completion before downloading.
• Rate limits apply by usage tier (do not list specific limits).
• Content restrictions are enforced by the API (see Guardrails below).

Guardrails (must enforce)

• Only content suitable for audiences under 18.
• No copyrighted characters or copyrighted music.
• No real people (including public figures).
• Input images with human faces are rejected.
• Character uploads in this skill are for non-human subjects only.

Prompt augmentation

Reformat prompts into a structured, production-oriented spec. Only make implicit details explicit; do not invent new creative requirements.

Template (include only relevant lines):

Use case: <where the clip will be used>
Primary request: <user's main prompt>
Scene/background: <location, time of day, atmosphere>
Subject: <main subject>
Action: <single clear action>
Camera: <shot type, angle, motion>
Lighting/mood: <lighting + mood>
Color palette: <3-5 color anchors>
Style/format: <film/animation/format cues>
Timing/beats: <counts or beats>
Audio: <ambient cue / music / voiceover if requested>
Text (verbatim): "<exact text>"
Dialogue:
<dialogue>
- Speaker: "Short line."
</dialogue>
Constraints: <must keep/must avoid>
Avoid: <negative constraints>

Augmentation rules:

• Keep it short; add only details the user already implied or provided elsewhere.
• For edits, explicitly list invariants ("same shot, change only X").
• For character-based shots, mention the character name verbatim in the prompt.
• If any critical detail is missing and blocks success, ask a question; otherwise proceed.
• If you pass a structured prompt file to the CLI, add --no-augment to avoid the tool re-wrapping it.

Examples

Generation example (single shot)

Use case: product teaser
Primary request: a close-up of a matte black camera on a pedestal
Action: slow 30-degree orbit over 4 seconds
Camera: 85mm, shallow depth of field, gentle handheld drift
Lighting/mood: soft key light, subtle rim, premium studio feel
Constraints: no logos, no text

Edit example (invariants)

Primary request: same shot and framing, switch palette to teal/sand/rust with warmer backlight
Constraints: keep the subject and camera move unchanged

Character consistency example

Primary request: Mossy, a moss-covered teapot mascot, hurries through a lantern-lit market at dusk
Camera: cinematic tracking shot, 35mm, shoulder height
Lighting/mood: warm dusk practicals, soft haze
Constraints: keep Mossy’s silhouette and moss texture consistent across the shot

Prompting best practices (short list)

• One main action + one camera move per shot.
• Use counts or beats for timing ("two steps, pause, turn").
• Keep text short and the camera locked-off for UI or on-screen text.
• Add a brief avoid line when artifacts appear (flicker, jitter, fast motion).
• Shorter prompts are more creative; longer prompts are more controlled.
• Put dialogue in a dedicated block; keep lines short for 4-8s clips.
• Mention character names verbatim when using uploaded character IDs.
• State invariants explicitly for edits (same shot, same camera move).
• Prefer edit for targeted changes and extend for timeline continuation.
• Iterate with single-change follow-ups to preserve continuity.

Guidance by asset type

Use these modules when the request is for a specific artifact. They provide targeted templates and defaults.

• Cinematic shots: references/cinematic-shots.md
• Social ads: references/social-ads.md

CLI + environment notes

• CLI commands + examples: references/cli.md
• API parameter quick reference: references/video-api.md
• Prompting guidance: references/prompting.md
• Sample prompts: references/sample-prompts.md
• Troubleshooting: references/troubleshooting.md
• Network/sandbox tips: references/codex-network.md

Reference map

• references/cli.md: how to run create/edit/extend/create-character/poll/download/local-queue flows via scripts/sora.py.
• references/video-api.md: API-level knobs (models, sizes, duration, characters, edits, extensions, official Batch API).
• references/prompting.md: prompt structure, character continuity, editing, and extension guidance.
• references/sample-prompts.md: copy/paste prompt recipes (examples only; no extra theory).
• references/cinematic-shots.md: templates for filmic shots.
• references/social-ads.md: templates for short social ad beats.
• references/troubleshooting.md: common errors and fixes.
• references/codex-network.md: network/approval troubleshooting.

Learning maintenance

Maintain references/learning-log.md for this skill.

Update it when:

• a user gives a reusable correction about this skill's trigger, scope, workflow, output, validation, or routing
• a novel multi-step workflow using this skill is approved for reuse
• a failed or brittle path reveals an avoided path worth preserving

Keep entries concise and generalizable. Record:

• durable rules
• approved workflow promotions
• avoided paths

Do not store full transcripts, transient facts, or one-off preferences.