A workflow for creating, changing, checking, listing, and downloading short videos through OpenAI’s Sora video API. An API lets software send requests to a service and receive results.

It is for creating videos from prompts, remixing existing videos, checking job status, downloading videos or previews, and generating batches of clips.

It organizes video jobs and provides a repeatable way to generate or manage clips for demos, product visuals, and other projects.

sora — Skill for Claude Code and Codex by tercumantanumut/selene

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add tercumantanumut/selene --skill sora

Clone the repo

git clone --depth 1 https://github.com/tercumantanumut/selene

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/tercumantanumut/selene/sora/github.svg)](https://agentmods.dev/skills/tercumantanumut/selene/sora)

Your own site

<a href="https://agentmods.dev/skills/tercumantanumut/selene/sora"><img src="https://agentmods.dev/badge/skills/tercumantanumut/selene/sora/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/tercumantanumut/selene/sora"><img src="https://agentmods.dev/badge/skills/tercumantanumut/selene/sora.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 91 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,097 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium Excessive Agency · line 42
Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00091	$0.02097
Opus 5.5	$0.00036	$0.00839
Sonnet 5.5	$0.00018	$0.00419
Haiku 4.5	$0.00009	$0.00210

Measured 2mo ago against content hash 451f0caf6656, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

sora scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/sora.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

lib/skills/catalog/bundled/sora/SKILL.md · 154 lines

How it starts

The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

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 (${SELENE_SKILL_ROOT}/scripts/sora.py) with sensible defaults (see ${SELENE_SKILL_ROOT}/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.

Read the full file on GitHub · 154 lines

Files

What ships with it

9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 154 lines · 91 tokens per session scan A 451f0caf6656

Subscribe to this mod's changes

sora is a skill published in the GitHub repository tercumantanumut/selene (173 stars, last pushed 3d ago), licensed MIT. It adds 91 tokens to every session and 2,097 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Creative and media LLM agent codebase-indexing diffusion-models knowledge-base long-term-memory

sora next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
soratercumantanumut/selene	Skill	173	3d ago	MIT	A	91	Claude Code, Codex
browserwing-executorMemTensor/MemOS	Skill	12k	yesterday	Apache-2.0	A	42	Claude Code, Codex
dev-browserMemTensor/MemOS	Skill	12k	yesterday	Apache-2.0	A	84	Claude Code, Codex
ask-user-questionMemTensor/MemOS	Skill	12k	yesterday	Apache-2.0	A	44	Claude Code, Codex
memos-memory-guideMemTensor/MemOS	Skill	12k	yesterday	Apache-2.0	A	131	Claude Code, Codex
browserwing-adminMemTensor/MemOS	Skill	12k	yesterday	Apache-2.0	B	47	Claude Code, Codex
computer-historyMemTensor/memmy-agent	Skill	2.2k	yesterday	MIT	A	42	Claude Code, Codex