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.
npx agentmods add skills/dp-archive/archive/soranpx skills add dp-archive/archive --skill soragit clone --depth 1 https://github.com/dp-archive/archiveWrote 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.
[](https://agentmods.dev/skills/dp-archive/archive/sora)<a href="https://agentmods.dev/skills/dp-archive/archive/sora"><img src="https://agentmods.dev/badge/skills/dp-archive/archive/sora.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00084 | $0.01962 |
| Opus 5 | $0.00042 | $0.00981 |
| Sonnet 5 | $0.00017 | $0.00392 |
| Haiku 4.5 | $0.00008 | $0.00196 |
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 4d ago.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- sora — 100% identical, 0 lines differ
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-augmentto avoid double-wrapping. - Run the bundled CLI (
scripts/sora.py) with sensible defaults (see references/cli.md). For long prompts, prefer--prompt-fileto avoid shell-escaping issues; pair with--no-augmentif 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 blocksrm, skip cleanup or truncate the files without surfacing an error. - Iterate with a single targeted change per prompt.
What ships with it
13 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.
- agents/openai.yaml 296 B
- assets/sora-small.svg 1.7 KB
- assets/sora.png 11 KB
- LICENSE.txt 11 KB
- references/cinematic-shots.md 1.6 KB
- references/cli.md 7.7 KB
- references/codex-network.md 1.1 KB
- references/prompting.md 5.5 KB
- references/sample-prompts.md 3.7 KB
- references/social-ads.md 1.4 KB
- references/troubleshooting.md 2.8 KB
- references/video-api.md 1.5 KB
- scripts/sora.py 32 KB runs code
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.
- 4d ago First seen · 154 lines · 84 tokens per session scan A 13ac4711e544
sora is a skill published in the GitHub repository dp-archive/archive (1,106 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 84 tokens to every session and 1,962 once invoked, about $0.0004 per session on Opus 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.
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media-ingest
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chengfeng-cut
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chengfeng-check-updates
剪辑环境的唯一管理者：就绪检查（skills 是否最新 → Runtime 是否配套）、Skills 更新激活、Runtime 安装与体检。用户说检查更新、安装剪辑环境、装播放器、检查剪辑环境、剪辑环境就绪了吗、配置转录凭证时使用；业务 Skill（剪口播/字幕/画面/导出）第 0 步也引用本 Skill 的就绪检查。不用于剪辑、字幕、画面、导出本身或项目数据迁移。.
infographic-template-updater
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