Shorts Video Maker
uxjoseph/content-marketing-team
YouTube 영상에서 쇼츠 클립 3개를 자동 제작합니다. An agent skill from uxjoseph/content-marketing-team.
“环境准备。安装依赖、下载模型、验证环境。触发词：安装、环境准备、初始化”
Install Videocut Install
$ npx skills add zrt-ai-lab/opencode-skills --skill videocut-install -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install zrt-ai-lab/opencode-skills videocut-install --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/zrt-ai-lab/opencode-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/videocut-install .claude/skills/videocut-install && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "videocut-install" agent skill from https://github.com/zrt-ai-lab/opencode-skills/tree/main/videocut-install into .claude/skills/videocut-install/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "videocut-install", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/zrt-ai-lab/opencode-skills/tree/main/videocut-installType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add zrt-ai-lab/opencode-skills --skill videocut-install -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install zrt-ai-lab/opencode-skills videocut-install --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zrt-ai-lab/opencode-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/videocut-install .agents/skills/videocut-install && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "videocut-install" agent skill from https://github.com/zrt-ai-lab/opencode-skills/tree/main/videocut-install into .agents/skills/videocut-install/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "videocut-install", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add zrt-ai-lab/opencode-skills --skill videocut-install -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install zrt-ai-lab/opencode-skills videocut-install --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zrt-ai-lab/opencode-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/videocut-install .cursor/skills/videocut-install && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "videocut-install" agent skill from https://github.com/zrt-ai-lab/opencode-skills/tree/main/videocut-install into .cursor/skills/videocut-install/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "videocut-install", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/zrt-ai-lab/opencode-skills.git --path videocut-install--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add zrt-ai-lab/opencode-skills --skill videocut-install -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install zrt-ai-lab/opencode-skills videocut-install --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zrt-ai-lab/opencode-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/videocut-install .gemini/skills/videocut-install && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "videocut-install" agent skill from https://github.com/zrt-ai-lab/opencode-skills/tree/main/videocut-install into .gemini/skills/videocut-install/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "videocut-install", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install zrt-ai-lab/opencode-skills videocut-installInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add zrt-ai-lab/opencode-skills --skill videocut-install -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/zrt-ai-lab/opencode-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/videocut-install .github/skills/videocut-install && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "videocut-install" agent skill from https://github.com/zrt-ai-lab/opencode-skills/tree/main/videocut-install into .github/skills/videocut-install/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "videocut-install", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add zrt-ai-lab/opencode-skills --skill videocut-install -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install zrt-ai-lab/opencode-skills videocut-install --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zrt-ai-lab/opencode-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/videocut-install .opencode/skills/videocut-install && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "videocut-install" agent skill from https://github.com/zrt-ai-lab/opencode-skills/tree/main/videocut-install into .opencode/skills/videocut-install/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "videocut-install", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
videocut-install- GitHub stars
- 287
- Token cost
- ~536 tokens
- SKILL.md length
- 95 words
- Files
- 2
- Skills in repo
- 26
- Repo updated
- First seen
- Licence
- None found
At a glance
- Works in 5 steps: 安装 Python 依赖 → 安装 FFmpeg → 下载 FunASR 模型（约2GB） → …
- SKILL.md covers 快速使用, 依赖清单, 模型清单 and 安装流程, plus 2 more sections
- Calls pip, brew and apt
About this skill
Videocut Install is a skill in zrt-ai-lab/opencode-skills (287 stars). Its SKILL.md is about 536 tokens, with 1 other file in the folder. No licence found.
Workflow steps
5 steps, taken from the step headings in SKILL.md.
- 安装 Python 依赖
- 安装 FFmpeg
- 下载 FunASR 模型（约2GB）
- 下载 Whisper 模型（约3GB）
- 验证环境
What it can do on your machine
Read from SKILL.md and the folder at commit d38536f. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
pipbrewaptffmpegpython3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Videocut Install loads about 536 tokens when it runs. Until then it costs about 13 tokens; SKILL.md has 95 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NoteRuns commands with sudoSKILL.md:94
sudo apt install ffmpeg
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
Without a licence we can't republish the file, so here is its outline and opening line. It has 95 words (~536 tokens).
“input: 无 output: 环境就绪 pos: 前置 skill，首次使用前运行”
- name
- videocut-install
- metadata.version
- 1.0.0
- metadata.alias
- videocut:安装
Files
SKILL.md and 1 other file in videocut-install of zrt-ai-lab/opencode-skills.
- SKILL.md
- README.md
Open the folder on GitHubat commit d38536f
Compare with similar skills
Videocut Install next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Videocut Install this skillzrt-ai-lab/opencode-skills | 287 | — | ~536 | Automated safety check: Notes | None | |
| Shorts Video Makeruxjoseph/content-marketing-team | 107 | — | ~665 | Automated safety check: Pass | None | |
| Bggg Tiktok Cutbinggandata/bggg-skills | 604 | — | ~954 | Automated safety check: Pass | MIT | |
| Lark Minutesrongxinzy/RongxinAI | 154 | 2 repos | ~2.1k | Automated safety check: Pass | AGPL-3.0 | |
| Caption Burngooseworks-ai/goose-skills | 1.2k | — | ~1.2k | Automated safety check: Pass | MIT | |
| Video Understandcalesthio/OpenMontage | 66k | — | ~841 | Automated safety check: Pass | AGPL-3.0 |
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Lark Minutes
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飞书妙记：搜索妙记、查看妙记基础信息、下载/上传音视频、读取或编辑妙记的产物内容、改标题、替换说话人/关键词、申请妙记查看/编辑权限。当给出minutetoken、本地音视频文件，要查/改/转妙记产物，或用户明确要主动申请妙记权限时使用；本地音视频转纪要/逐字稿优先走本 skill，不要用 ffmpeg/whisper 本地转写。不负责：获取会议关联妙记，或仅按自然语言标题定位纪要
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Works with
Categories
Questions about Videocut Install
How do I install Videocut Install in Claude Code?
Run `npx skills add zrt-ai-lab/opencode-skills --skill videocut-install -a claude-code`. Or copy the skill folder (videocut-install in zrt-ai-lab/opencode-skills) into .claude/skills/videocut-install in your project. Claude Code loads it when a task matches its description.
How do I install Videocut Install in Codex?
Run `npx skills add zrt-ai-lab/opencode-skills --skill videocut-install -a codex`. Or copy the skill folder (videocut-install in zrt-ai-lab/opencode-skills) into .agents/skills/videocut-install in your project. Codex loads it when a task matches its description.
Can I use Videocut Install in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add zrt-ai-lab/opencode-skills --skill videocut-install -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/videocut-install, .gemini/skills/videocut-install, .github/skills/videocut-install and .opencode/skills/videocut-install in your project.
What does Videocut Install need to run?
Going by SKILL.md and its folder, Videocut Install needs the command-line tools its instructions call (pip, brew, apt, ffmpeg and python3).
Does Videocut Install access the network?
SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Videocut Install safe to install?
Our automated static check of SKILL.md found notes only (runs commands with sudo), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Videocut Install use?
No licence was found for Videocut Install or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Videocut Install use?
About 536 tokens (SKILL.md is roughly 2.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Videocut Install?
Skills that share tags, products or a category with Videocut Install: Shorts Video Maker (uxjoseph/content-marketing-team, 107 stars), Bggg Tiktok Cut (binggandata/bggg-skills, 604 stars), Lark Minutes (rongxinzy/RongxinAI, 154 stars) and Caption Burn (gooseworks-ai/goose-skills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Videocut Install?
zrt-ai-lab (a GitHub user) maintains it in zrt-ai-lab/opencode-skills, which has 287 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on July 22, 2026.
Source: zrt-ai-lab/opencode-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.