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 skills add Jaycheng1103/chatgpt-video-editing-skills --skill chatgpt-video-editing-setupgit clone --depth 1 https://github.com/Jaycheng1103/chatgpt-video-editing-skillsWrote 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/jaycheng1103/chatgpt-video-editing-skills/chatgpt-video-editing-setup)<a href="https://agentmods.dev/skills/jaycheng1103/chatgpt-video-editing-skills/chatgpt-video-editing-setup"><img src="https://agentmods.dev/badge/skills/jaycheng1103/chatgpt-video-editing-skills/chatgpt-video-editing-setup/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.
<a href="https://agentmods.dev/skills/jaycheng1103/chatgpt-video-editing-skills/chatgpt-video-editing-setup"><img src="https://agentmods.dev/badge/skills/jaycheng1103/chatgpt-video-editing-skills/chatgpt-video-editing-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00096 | $0.00742 |
| Opus 5 | $0.00048 | $0.00371 |
| Sonnet 5 | $0.00019 | $0.00148 |
| Haiku 4.5 | $0.00010 | $0.00074 |
Grade A, and why
chatgpt-video-editing-setup 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 13d 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.
How it starts
The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ChatGPT Video Editing Setup
Prepare or repair the environment without starting creative work. The outcome is an evidence-backed readiness report, not a transcript, upload, edit, preview, or render.
Read first
Read the setup runbook for commands and install choices. Read security and verification before handling credentials or declaring anything ready.
Operating sequence
- Inspect before changing anything: check the stable paths
~/Developer/video-useand, only when requested,~/Developer/hyperframes. Recognize normal checkouts and linked worktrees withgit rev-parse, then capture each repository's exact origin, branch or detached state, commit, and status. Also check available runtime tools, the Source Han Sans TW subtitle font in the user's font directory, and the active agent's Skills location. Do not print secrets. - Treat any existing path that is not a Git worktree as a hard stop. The only accepted origins are the exact official HTTPS URLs in the runbook. A missing or different origin and a dirty status are also hard stops: report the evidence, never rewrite the remote automatically, and do not pull, reset, overwrite, install dependencies, or register a Skill.
- State the exact mutations needed, including clones, package installs, font downloads, large downloads, or Skills-directory changes. Obtain explicit approval before any of them. Inspection and a no-cost local version check do not imply approval to mutate.
- After approval, follow the runbook exactly and repeat the repository preflight immediately before dependency installation or Skill registration. Install/register the complete video-use repository so its helpers remain available. Install the Source Han Sans TW subtitle font only from the official Adobe Fonts repository, never overwriting an existing font file. Treat HyperFrames as optional unless the user specifically needs HTML, CSS, or GSAP animation; when requested, require Node.js 22 or newer.
- Configure ElevenLabs only through an existing environment variable or the
protected
~/Developer/video-use/.envpath. Never echo, log, or commit a credential. - Verify with local, no-paid-work checks only, including the subtitle font files. Run HyperFrames repository, Node, lockfile, and Core Skills checks only if HyperFrames was explicitly approved and installed; otherwise report it as not requested. Do not upload media, call transcription, create an edit directory, or edit/render video.
- Report checked paths, approved mutations performed, evidence, versions or command outcomes, remaining gaps, and the explicit next action. Never claim readiness without successful evidence.
What ships with it
2 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.
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.
- 13d ago First seen · 61 lines · 96 tokens per session scan A 79cf3d680c1d
chatgpt-video-editing-setup is a skill published in the GitHub repository Jaycheng1103/chatgpt-video-editing-skills (530 stars, last pushed 1mo ago), licensed MIT. It adds 96 tokens to every session and 742 once invoked, about $0.0005 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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