Sora

Sora Video Generation Skill

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.

When to use

• 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)

Decision tree (create vs remix vs status/download vs batch)

• 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)

Workflow

1. Decide intent: create vs remix vs status/download vs batch.
2. Collect inputs: prompt, model, size, seconds, and any input reference image.
3. If batch: write a temporary JSONL under tmp/ (one job per line), run once, then delete the JSONL.
4. 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.
5. 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.
6. For async jobs, poll until complete (or use create-and-poll).
7. Download assets (video/thumbnail/spritesheet) and save locally.
8. 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.
9. Iterate with a single targeted change per prompt.

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" as strings).
• Always set size and seconds via API params; prose will not change them.
• Use the OpenAI Python SDK (openai package); do not use raw HTTP.
• 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.
• Download URLs expire after about 1 hour; copy assets to your own storage.
• 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 is limited to 4/8/12 seconds and must be set via the seconds parameter.
• The API expects seconds as a string enum ("4", "8", "12").
• 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.

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: 
Primary request: 
Scene/background: 
Subject: 
Action: 
Camera: 
Lighting/mood: 
Color palette: 
Style/format: 
Timing/beats: 
Audio: 
Text (verbatim): ""
Dialogue:

- Speaker: "Short line."

Constraints: 
Avoid: 

Augmentation rules:

• Keep it short; add only details the user already implied or provided elsewhere.
• For remixes, explicitly list invariants ("same shot, change only X").
• 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

Remix 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

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.
• State invariants explicitly for remixes (same shot, same camera move).
• 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/poll/remix/download/batch via scripts/sora.py.
• references/video-api.md: API-level knobs (models, sizes, duration, variants, status).
• references/prompting.md: prompt structure and iteration 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.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: dp-archive
• Source: dp-archive/archive
• License: Apache-2.0

Install and usage instructions live in the source repository linked above.