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openai/sora

openai

sora

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.

global
0installs0uses~2.6k
v2.1Saved Apr 20, 2026

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.
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Overall Score

88/100

Grade

A

Excellent

Safety

92

Quality

87

Clarity

85

Completeness

86

Summary

A comprehensive skill for generating, editing, extending, and managing Sora AI video clips. The skill provides a structured workflow using the bundled CLI (`scripts/sora.py`), prompt augmentation templates, character reference management, and local batch queuing. It enforces guardrails around content (no copyrighted material, no real people), requires OpenAI API credentials, and supports both immediate rendering and official Batch API integration.

Detected Capabilities

Async video job creation and polling via OpenAI Video APIStructured prompt augmentation with scene, camera, lighting, and dialogue fieldsVideo editing (targeted changes to completed videos)Video extension (timeline continuation up to 120 seconds total)Character reference upload and reuse (non-human subjects only)Asset download (video MP4, thumbnail webp, spritesheet jpg)Local concurrent batch job fan-out (create-batch)Job listing, status retrieval, and deletionInput reference guidance (image anchors for first frame)Multi-character composition (up to 2 per generation)Model and size selection (sora-2, sora-2-pro with resolution limits)

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

generate videoedit Sora videoextend videocreate character referencevideo status pollingdownload video assetbatch video queueSora API key setup

Risk Signals

INFO

OPENAI_API_KEY environment variable required for live API calls

SKILL.md, Authentication section; scripts/sora.py lines ~150-160
INFO

Network outbound requests to OpenAI Video API (platform.openai.com)

scripts/sora.py, _create_client() and video API calls throughout
INFO

File I/O operations: reading prompts from --prompt-file, writing JSON responses to disk

scripts/sora.py, _read_prompt(), _write_download(), _job_output_path()
INFO

Multipart file upload for character reference and input image uploads

scripts/sora.py, _open_input_reference(), _open_video_upload(), _video_post()
INFO

Shell escaping mitigation: --prompt-file recommended for multi-line prompts to avoid shell injection

SKILL.md, Workflow section; references/troubleshooting.md
INFO

Content guardrails enforced: only audiences under 18, no copyrighted characters/music, no real people, no human faces in input images

SKILL.md, Guardrails section
INFO

Download URLs expire after ~1 hour; users must save assets promptly

SKILL.md, Defaults & rules; references/video-api.md
INFO

Rate limiting and API access restrictions apply; organization-verified account required

SKILL.md, API limitations section
INFO

UV cache permission fallback documented: UV_CACHE_DIR=/tmp/uv-cache for CI/sandbox environments

SKILL.md, Defaults & rules; references/troubleshooting.md
INFO

No credential exfiltration: skill does not log, output, or transmit API keys; only reads from environment

scripts/sora.py, _ensure_api_key()

Referenced Domains

External domains referenced in skill content, detected by static analysis.

platform.openai.comwww.apache.org

Use Cases

  • Generate product demo videos and marketing clips
  • Create reusable non-human character references for consistent visual branding
  • Edit completed Sora videos with targeted prompt changes while preserving framing
  • Extend completed videos with continuation prompts for multi-beat storytelling
  • Manage video job status, polling, and asset downloads (video/thumbnail/spritesheet)
  • Plan and execute multi-video batch queues locally or via official Batch API
  • Create cinematic shots with structured prompt templates
  • Generate short social media ads with beat-based timing

Quality Notes

  • POSITIVE: Comprehensive decision tree guides agents to choose the correct workflow (create vs edit vs extend vs create-character) based on user intent.
  • POSITIVE: Structured prompt augmentation template with clear sections (Use case, Primary request, Scene, Subject, Action, Camera, Lighting, Palette, Style, Audio, Dialogue, Constraints, Avoid) reduces ambiguity and improves video consistency.
  • POSITIVE: Extensive reference documentation (7 markdown files) provides targeted guidance: cinematic shots, social ads, prompting best practices, sample prompts, CLI reference, API quick reference, troubleshooting.
  • POSITIVE: Security guardrails explicitly documented (no real people, no copyrighted material, no audiences under 18) and enforced at API level.
  • POSITIVE: Clear distinction between local `create-batch` fan-out and official Batch API with guidance on when to use each.
  • POSITIVE: Error handling patterns documented for common failures: size/seconds validation, SDK lag, permission errors, prompt escaping, input reference rejection, character continuity issues, extension drift.
  • POSITIVE: Dry-run mode (`--dry-run`) allows testing without API calls or network access.
  • POSITIVE: CLI defaults are sensible (sora-2, 1280x720, 4 seconds, 10s poll interval) with clear overrides.
  • POSITIVE: Augmentation rules prevent double-wrapping when prompts are already structured; `--no-augment` flag avoids re-wrapping.
  • POSITIVE: Character workflow limited to non-human subjects only, with clear constraints on MP4 format, duration, resolution, and aspect ratio.
  • QUALITY_NOTE: `scripts/sora.py` is 42 KB; for an agent skill, this is appropriate complexity, but the file could benefit from inline docstring examples at function level to aid agent understanding of error conditions.
  • QUALITY_NOTE: Polling timeout and retry logic for rate-limit errors is well-implemented (_extract_retry_after_seconds, _is_transient_error) but could have clearer logging output for long-running jobs.
  • QUALITY_NOTE: Extension limitations (no characters, no image references, max 6x extensions = 120s total) are documented but could be clearer in the main skill description for quick reference.
  • QUALITY_NOTE: Batch-generated videos expire after 24 hours; this is noted in video-api.md but should be surfaced in the main skill for batch workflows.
  • QUALITY_NOTE: Multi-shot prompts are mentioned in references/prompting.md but not in the main skill; unclear if the API supports multi-shot generation or if prompts are for single shots only.
Model: claude-haiku-4-5-20251001Analyzed: Apr 20, 2026

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Version History

v2.1

Content updated

2026-04-20

Latest
v2.0

Content updated from upstream GitHub source

2026-03-29

v1.0

Seeded from github.com/openai/skills

2026-03-16

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