Agent skill

Videohub Story Editor

by cacity in cacity/VideoHub

把长视频或已有字幕转成有完整叙事的几分钟短片。先基于原文字幕和画面证据理解、选段与重排,再对最终时间轴重新翻译和可选润色;既可输出保留原声的双语字幕版,也可把原声降到 30% 并用 MiniMax 或豆包 TTS 生成影视解说、短剧混剪、播客串讲或知识解读版。已有项目可进入本地五轨时间线继续调整切点、旁白、原声窗口、字幕、音量和转场,并按修订版本渲染。用于“把长视频讲成短故事”“按字幕自动剪辑”…

MITAuto-check: notesMedia & Creative

Install Videohub Story Editor

skills CLI
$ npx skills add cacity/VideoHub --skill videohub-story-editor -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install cacity/VideoHub videohub-story-editor --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/cacity/VideoHub.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/videohub-story-editor .claude/skills/videohub-story-editor && rm -rf skills-src

Use ~/.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/

Facts

Skill name
videohub-story-editor
GitHub stars
168
Token cost
~2.3k tokens
SKILL.md length
307 words
Files
18 (incl. scripts, references)
Skills in repo
12
Repo updated
First seen
Licence
MIT

At a glance

把长视频或已有字幕转成有完整叙事的几分钟短片。先基于原文字幕和画面证据理解、选段与重排,再对最终时间轴重新翻译和可选润色;既可输出保留原声的双语字幕版,也可把原声降到 30% 并用 MiniMax 或豆包 TTS 生成影视解说、短剧混剪、播客串讲或知识解读版。已有项目可进入本地五轨时间线继续调整切点、旁白、原声窗口、字幕、音量和转场,并按修订版本渲染。用于“把长视频讲成短故事”“按字幕自动剪辑”…

  • Works in 8 steps: 证据提取层 → 故事理解层 → 剪辑规划层 → …
  • Tasks that involve Text to speech and voice
  • SKILL.md covers 边界, 默认值, 剧集素材项目目录 and 可视化时间线精修, plus 8 more sections
  • Runs Python scripts from its folder; calls python and npm; needs DEEPSEEK_API_KEY and MINIMAX_API_KEY

What it does

Videohub Story Editor is an agent skill from cacity/VideoHub. 把长视频或已有字幕转成有完整叙事的几分钟短片。先基于原文字幕和画面证据理解、选段与重排,再对最终时间轴重新翻译和可选润色;既可输出保留原声的双语字幕版,也可把原声降到 30% 并用 MiniMax 或豆包 TTS 生成影视解说、短剧混剪、播客串讲或知识解读版。已有项目可进入本地五轨时间线继续调整切点、旁白、原声窗口、字幕、音量和转场,并按修订版本渲染。用于“把长视频讲成短故事”“按字幕自动剪辑”“剪好后再翻译”“制作 TTS 解说版”“可视化精修”“生成抖音发布文件夹和文案”等任务。

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 20 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/editing-strategies.md` and `references/model-workflow.md`).

It sits in Media & Creative, covering Text to speech and voice, Video production and Transcription. It works with MiniMax and FFmpeg. The repository describes itself as: VideoHub 是一款本地化多平台视频处理与智能剪辑工具,支持 YouTube、抖音/TikTok、Instagram、Bilibili 和 Twitter/X,提供视频下载、Whisper 转写、字幕翻译与润色、多模型 AI 配音、影视解说、故事剪辑、音乐卡点及剧集批量处理,并可通过 Codex、Claude Code… The licence is MIT.

When your agent uses it

  • Tasks that involve Text to speech and voice
  • Tasks that involve Video production
  • Tasks that involve Transcription

Example prompts

  • “把长视频讲成短故事”
  • “按字幕自动剪辑”
  • “剪好后再翻译”
  • “/videohub-story-editor”

Requirements

  • Python 3
  • Node.js
  • A credential in DEEPSEEK_API_KEY
  • A credential in MINIMAX_API_KEY

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. 证据提取层
  2. 故事理解层
  3. 剪辑规划层
  4. 剪辑后翻译
  5. 原声版
  6. TTS 解说版
  7. 确定性渲染和交付
  8. 抖音发布包

What it can do on your machine

Read from SKILL.md and the folder at commit d1da59c. 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

    Ships 11 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python
    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npm, 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 these keys or tokens, usually read from environment variables:

    • DEEPSEEK_API_KEY
    • MINIMAX_API_KEY
    • DOUBAO_TTS_ACCESS_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Videohub Story Editor loads about 2.3k tokens when it runs, and up to ~9.5k if it reads all its reference files. Until then it costs about 67 tokens; SKILL.md has 307 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~67
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.5k

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.

  • NoteMentions a .env fileSKILL.md:240
    或 `.env`,不要写进 JSON。

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); the scripts in this folder are not scanned.

SKILL.md

The full file from cacity/VideoHub at commit d1da59c, republished under its MIT licence (© cacity). 307 words, ~2,293 tokens.

Download SKILL.mdSave it as .claude/skills/videohub-story-editor/SKILL.md (or your agent's skills folder). This skill also uses 17 other files; get the full folder from GitHub.
name
videohub-story-editor
description
把长视频或已有字幕转成有完整叙事的几分钟短片。先基于原文字幕和画面证据理解、选段与重排,再对最终时间轴重新翻译和可选润色;既可输出保留原声的双语字幕版,也可把原声降到 30% 并用 MiniMax 或豆包 TTS 生成影视解说、短剧混剪、播客串讲或知识解读版。已有项目可进入本地五轨时间线继续调整切点、旁白、原声窗口、字幕、音量和转场,并按修订版本渲染。用于“把长视频讲成短故事”“按字幕自动剪辑”“剪好后再翻译”“制作 TTS 解说版”“可视化精修”“生成抖音发布文件夹和文案”等任务。

VideoHub Story Editor

使用以下固定结构,不直接让模型凭摘要调用 FFmpeg:

text
视频和原文字幕
  -> 证据提取层
  -> 故事理解层
  -> 剪辑规划层
  -> 最终原文时间轴
  -> 后置翻译和可选润色
  -> 原声版 / TTS 解说版
  -> 确定性渲染和 QA
  -> 抖音发布包(可选)

边界

  • 不安装或调用 WhisperX。
  • 优先使用人工字幕或平台字幕;缺少字幕时,调用 videohub-youtube 和 src/youtube_transcriber.py 的现有 Whisper 流程。
  • 故事理解和选段以原文字幕为证据。不要依赖剪辑前的逐句机翻决定剧情、因果或 说话人意图。
  • 模型负责理解、选段和撰写解说;脚本负责时间计算、证据校验、翻译接入、TTS 对齐、渲染和 QA。
  • 原声版和解说版必须复用同一个 story_plan.json,避免两套版本选段漂移。
  • 翻译或 TTS 凭据缺失时,不得阻断证据提取、故事计划和原声原文版。
  • 默认先交付分析与剪辑方案;用户明确要求成片后才执行渲染。
  • 只处理用户有权下载和再创作的内容。

默认值

  • 目标时长:240 秒,容差 15%。
  • 输出语言:简体中文。
  • 外文视频:剪辑后翻译,原声版默认双语字幕。
  • 解说版:中文 TTS 字幕,原声音量 0.30。
  • 播放速度:1.0 倍,不为凑时长自动改变原片对白速度。
  • 分析目录:workspace/review_packs/story_editor/<job_id>/。
  • 成片目录:workspace/videos_with_subtitles/ 或计划中的输出目录。
  • 抖音发布包:workspace/publish_packages/douyin/<package_name>/。

剧集素材项目目录

用户只提供一个剧集目录时,不再要求分别提供视频和字幕路径。先刷新目录内的可移植项目清单:

powershell
python src/series_project.py "<series_dir>"

读取 <series_dir>/videohub_project.json,按用户给出的集数或文件名选择 episodes 中的条目。 视频位于项目根目录;本地批处理生成的字幕位于 subtitles/。选择字幕时依次优先使用:

  1. subtitles.polished 中的 SRT。
  2. subtitles.translated 中与目标语言匹配的 SRT。
  3. subtitles.source 中的 SRT。
  4. 视频内嵌字幕;仍没有字幕时再调用 VideoHub Whisper 流程。

清单只保存相对路径,移动整个剧集目录后仍可使用。空格、下划线、连字符以及 _google、_polished、语言后缀的差异由项目扫描器归一化匹配。目录包含多集而用户未说明 集数时,必须先确认目标集,不能默认把整季当成一个视频任务。

可视化时间线精修

已有解说项目完成 AI 初剪后,可以启动本地网页工作台:

powershell
cd frontend
npm install
npm run build
cd ..
python src/story_timeline_server.py

打开 http://127.0.0.1:8766/story-editor,选择包含 docs/story_job/story_plan.json 的 workspace/projectNNN_* 项目。工作台导入故事计划、 旁白计划、字幕和证据文件,显示视频、原声、TTS 旁白、原声锚点和字幕五条轨道。

  • 可以预览素材,拖动切点,拆分、删除和重排片段,并撤销或重做。
  • 可以修改旁白文本、单独调用 MiniMax 重生成一个语音块,拖动原声窗口和字幕边界; 预览画面中的解说字幕可上下拖动,避开原片已有的硬字幕,保存后按同一位置烧录。
  • 可以设置片段音量关键帧、淡入淡出、交叉转场,并注册其他本地视频源。
  • 配置 DEEPSEEK_API_KEY 后可以对选中的旁白做保守局部改写;缺少密钥时不影响其他功能。
  • 保存会写入项目的 revisions/rev-*;片段缓存写入 .story_editor_cache/segments。 不覆盖源视频、原始计划、原始字幕或已有 TTS 文件。

时间线编辑器是人工精修入口。对剧情、人物和因果的判断仍应先执行下面的证据提取与故事 理解流程,不能用拖动时间线替代证据校验。

1. 证据提取层

确认视频和带时间码的原文字幕存在。没有字幕时先使用 VideoHub 现有字幕流程。

powershell
python .agents/skills/videohub-story-editor/scripts/build_evidence_pack.py `
  --video "<video_path>" `
  --subtitle "<source_subtitle.srt>" `
  --language "<source_language>" `
  --target-language "zh-CN"

新任务默认不要传 --translated-subtitle。该参数只用于兼容已经有可靠译文的旧任务。 脚本输出 evidence_pack.json、transcript.json、scenes.json、关键帧和 analysis_chunks/chunk-*.json。

场景检测或抽帧成本过高时可使用 --skip-scene-detection 或 --skip-keyframes, 但必须在分析的不确定性中说明视觉证据缺失。

2. 故事理解层

读取 story-analysis-schema.md 和 editing-strategies.md。

  1. 逐个读取 analysis_chunks,记录人物或说话人、事件、观点、问题、答案、步骤和结果。
  2. 实际检查关键帧后再填写视觉发现;未看画面时不得猜测动作、表情或地点。
  3. 汇总全片时间线、因果关系、主题、指代和连续性约束。
  4. 提出一到三个故事方案,选择一个方案。
  5. 所有结论保留 sub-*、scene-*、frame-*、visual-* 或 chunk-* 引用。

Codex、Claude Code 或 DeepSeek 都必须写出同一数据契约的 story_analysis.json。 调用 API 模型时,按 model-workflow.md 分批提交证据, 不要让供应商响应格式进入后续脚本。

powershell
python .agents/skills/videohub-story-editor/scripts/validate_story_analysis.py `
  "<job_dir>/story_analysis.json" `
  --evidence "<job_dir>/evidence_pack.json"

有错误时不得进入剪辑规划。

3. 剪辑规划层

根据选中的故事方案创建 story_plan.draft.json。读取 story-plan-schema.md,外文视频默认设置:

json
{
  "subtitle_mode": "bilingual",
  "translation_stage": "post_edit",
  "translation_polish": true
}

每个片段填写 kind、story_role、源时间范围、analysis_refs、 story_reason、audio_mode 和 transition。对白片段优先显式列出 source_subtitle_ids。允许重排,但不能改变事实、因果、教程步骤、问题与回答关系, 或拼出说话者没有表达过的观点。

powershell
python .agents/skills/videohub-story-editor/scripts/compile_story_plan.py `
  "<job_dir>/story_plan.draft.json" `
  --evidence "<job_dir>/evidence_pack.json" `
  --analysis "<job_dir>/story_analysis.json" `
  --output "<job_dir>/story_plan.json"

python .agents/skills/videohub-story-editor/scripts/validate_story_plan.py `
  "<job_dir>/story_plan.json" `
  --evidence "<job_dir>/evidence_pack.json" `
  --analysis "<job_dir>/story_analysis.json"

同时交付 story_outline.md 和 story_source_map.csv 供人工审核。校验错误必须修正; 警告必须解释或修正。

4. 剪辑后翻译

先按最终选段和重排顺序重建原文 SRT:

powershell
python .agents/skills/videohub-story-editor/scripts/prepare_story_subtitles.py `
  "<job_dir>/story_plan.json" `
  --evidence "<job_dir>/evidence_pack.json" `
  --analysis "<job_dir>/story_analysis.json" `
  --output "<job_dir>/final_source.srt"

source_subtitle_ids 是剧情证据引用,不保证覆盖片段里的全部对白。影视解说需要在底部 持续显示完整原声字幕时,渲染器必须使用 --source-subtitle-policy all-intersecting,按每个 入选片段的源时间范围收集并裁切全部相交字幕。默认 explicit 保持证据引用模式,兼容已有 计划。

再翻译最终 SRT。translation_polish=true 或显式 --polish 时,复用 VideoHub 现有的 Google 基础翻译和 DeepSeek 全局轻度润色,并保留可对比的基础翻译与润色版。

powershell
python .agents/skills/videohub-story-editor/scripts/translate_story_subtitles.py `
  "<job_dir>/story_plan.json" `
  --source "<job_dir>/final_source.srt" `
  --output "<job_dir>/final_zh-CN.srt" `
  --polish

没有 DEEPSEEK_API_KEY 时自动跳过润色并保留基础翻译;翻译失败也不能破坏已经生成的 原文字幕、故事计划或源视频。脚本生成 post_edit_translation.json 记录实际状态。

5. 原声版

原声版保留原片声音,并把剪辑后翻译注入最终时间轴:

powershell
python .agents/skills/videohub-story-editor/scripts/render_story.py `
  "<job_dir>/story_plan.json" `
  --evidence "<job_dir>/evidence_pack.json" `
  --analysis "<job_dir>/story_analysis.json" `
  --translated-subtitle "<job_dir>/final_zh-CN.srt" `
  --burn-subtitles bilingual `
  --subtitle-prefix "<job_dir>/source_audio" `
  --output "<output_dir>/<name>_source_audio.mp4" `
  --qa-report "<job_dir>/source_audio_qa.md"

--burn-subtitles 允许 none、source、translated、bilingual。外文视频烧录 译文或双语字幕时,必须提供覆盖全部最终字幕条目的后置翻译。

6. TTS 解说版

读取 narration-plan-schema.md,根据完整故事分析、 剪辑计划和来源映射撰写 narration_plan.json。解说可以串联和概括选中内容,但每个 叙述块都必须引用证据,不能虚构原片没有提供的事实。

电影、电视剧或短剧需要“第三者旁白为主、关键场面恢复影视原声”时,改用 videohub-film-commentary Skill。它仍复用本流程,但会增加不与旁白重叠的 source_audio_windows、动态原声音量和合并字幕。

powershell
python .agents/skills/videohub-story-editor/scripts/validate_narration_plan.py `
  "<job_dir>/narration_plan.json" `
  --story-plan "<job_dir>/story_plan.json" `
  --evidence "<job_dir>/evidence_pack.json" `
  --analysis "<job_dir>/story_analysis.json"

MiniMax 使用 MINIMAX_API_KEY;豆包使用 DOUBAO_TTS_APP_ID、 DOUBAO_TTS_ACCESS_TOKEN,可选 DOUBAO_TTS_RESOURCE_ID。凭据只放在本地环境变量 或 .env,不要写进 JSON。

powershell
python .agents/skills/videohub-story-editor/scripts/synthesize_story_narration.py `
  "<job_dir>/narration_plan.json" `
  --story-plan "<job_dir>/story_plan.json" `
  --evidence "<job_dir>/evidence_pack.json" `
  --analysis "<job_dir>/story_analysis.json"

合成器按文案和音色缓存分段 WAV,校验实际时长,生成与最终成片对齐的完整旁白轨和 中文字幕。然后渲染解说版:

powershell
python .agents/skills/videohub-story-editor/scripts/render_story.py `
  "<job_dir>/story_plan.json" `
  --evidence "<job_dir>/evidence_pack.json" `
  --analysis "<job_dir>/story_analysis.json" `
  --narration-audio "<job_dir>/narration_audio_minimax.wav" `
  --narration-subtitle "<job_dir>/narration_minimax.srt" `
  --background-volume 0.30 `
  --burn-subtitles translated `
  --subtitle-prefix "<job_dir>/narration_minimax" `
  --output "<output_dir>/<name>_narration_minimax.mp4" `
  --qa-report "<job_dir>/narration_minimax_qa.md"

豆包版本将文件名中的 minimax 换成 doubao。默认把原声降到 30%,但保留环境声、 音乐和关键对白。叙述文本过长时先改写;只有在不超过计划上限时才自动轻度加速。

7. 确定性渲染和交付

渲染器必须:

  • 只接受校验通过且来源指纹一致的计划。
  • 按原片时间范围重新编码片段并按 output_order 拼接。
  • 根据片段交集裁切原字幕,并换算到重排后的输出时间轴。
  • 分别输出原声版和解说版字幕、成片及 QA 报告,不互相覆盖。
  • 完整解码成片,检查时长和字幕边界;QA 通过后才清理中间片段。
  • 不删除源视频、证据包、计划和 TTS 缓存。

当前渲染器支持普通切换和 crossfade,也支持片段级视频/音频淡入淡出、音量关键帧、 片段缓存以及多个本地视频源。多个来源会统一到主视频的分辨率和帧率后再拼接。旧计划中的 fade 转场不会被当作独立转场类型;需要淡入淡出时,应设置片段的 fade_in_sec 和 fade_out_sec。

至少交付:

  • evidence_pack.json
  • story_analysis.json
  • story_plan.json
  • story_outline.md
  • story_source_map.csv
  • 原声版 MP4、最终原文/译文/双语字幕和 QA 报告
  • 请求解说版时,再交付 narration_plan.json、TTS 音轨、中文字幕、解说版 MP4 和 QA 报告

8. 抖音发布包

用户要求“适合发到抖音的文件夹”“发布包”或“配一段发布文案”时,在成片 QA 通过后 生成发布包。先根据 story_analysis.json、最终解说稿和实际成片撰写 50-100 个可见字符 的中文文案:概括具体内容和看点,不虚构结论,不使用与视频无关的夸张标题;话题标签 单独保存,不用标签凑文案长度。

powershell
python .agents/skills/videohub-story-editor/scripts/build_douyin_publish_package.py `
  "<final_video.mp4>" `
  --title "<发布标题>" `
  --caption "<50-100字中文文案>" `
  --hashtag "<话题1>" `
  --hashtag "<话题2>" `
  --source-url "<source_url>" `
  --qa-report "<job_dir>/qa.md" `
  --cover-time <representative_second>

发布包至少包含:

  • 经过媒体探测的 H.264/AAC MP4;已符合要求时优先硬链接,避免重复占用空间。
  • caption.txt:仅保存 50-100 字正文。
  • hashtags.txt:独立保存建议话题。
  • cover.jpg:用户要求或有合适代表画面时生成。
  • publish_notes.md:供人工发布前检查。
  • publish_manifest.json:记录媒体参数、文案长度、来源、QA 报告和 SHA-256。

横版成片默认保持原构图和 1080P,不自动强裁为竖屏。用户明确要求竖版时,应先重新 设计画面布局并完成单独 QA,不能直接裁掉人物、字幕或关键物体。发布前仍需人工检查 平台规则、版权授权、标题、封面和字幕。

不得把重排前的字幕时间码直接复制到成片。每个成片片段、原声字幕和解说块都必须 能回溯到原视频时间范围或证据 ID。

© cacity, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 17 other files (scripts, references) in .agents/skills/videohub-story-editor of cacity/VideoHub.

  • SKILL.md
  • agents/openai.yaml
  • references/editing-strategies.md
  • references/model-workflow.md
  • references/narration-plan-schema.md
  • references/story-analysis-schema.md
  • references/story-plan-schema.md
  • scripts/build_douyin_publish_package.py
  • scripts/build_evidence_pack.py
  • scripts/compile_story_plan.py
  • scripts/prepare_story_subtitles.py
  • scripts/render_story.py
  • scripts/story_pipeline_common.py
  • scripts/synthesize_story_narration.py
  • scripts/translate_story_subtitles.py
  • scripts/validate_narration_plan.py
  • scripts/validate_story_analysis.py
  • scripts/validate_story_plan.py

Open the folder on GitHubat commit d1da59c

Compare with similar skills

Videohub Story Editor 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.

Videohub Story Editor compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Videohub Story Editor this skillcacity/VideoHub168—~2.3kAutomated safety check: NotesMIT
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Explain Videolimin112/min-skill454—~2.4kAutomated safety check: PassNone
Qiaomu Cutjoeseesun/qiaomu-cut-skill372—~6.8kAutomated safety check: NotesMIT
ShowtimeFavioVazquez/showtime220—~3kAutomated safety check: PassMIT
Content To Videoarchitectds/modeldock117—~2.4kAutomated safety check: PassApache-2.0

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Works with

Questions about Videohub Story Editor

What does Videohub Story Editor do?

把长视频或已有字幕转成有完整叙事的几分钟短片。先基于原文字幕和画面证据理解、选段与重排,再对最终时间轴重新翻译和可选润色;既可输出保留原声的双语字幕版,也可把原声降到 30% 并用 MiniMax 或豆包 TTS 生成影视解说、短剧混剪、播客串讲或知识解读版。已有项目可进入本地五轨时间线继续调整切点、旁白、原声窗口、字幕、音量和转场,并按修订版本渲染。用于“把长视频讲成短故事”“按字幕自动剪辑”…. Videohub Story Editor is an agent skill from cacity/VideoHub.

When should I use Videohub Story Editor?

Videohub Story Editor fits situations like: tasks that involve Text to speech and voice; tasks that involve Video production; tasks that involve Transcription.

How do I install Videohub Story Editor in Claude Code?

Run `npx skills add cacity/VideoHub --skill videohub-story-editor -a claude-code`. Or copy the skill folder (.agents/skills/videohub-story-editor in cacity/VideoHub) into .claude/skills/videohub-story-editor in your project. Claude Code loads it when a task matches its description.

How do I install Videohub Story Editor in Codex?

Run `npx skills add cacity/VideoHub --skill videohub-story-editor -a codex`. Or copy the skill folder (.agents/skills/videohub-story-editor in cacity/VideoHub) into .agents/skills/videohub-story-editor in your project. Codex loads it when a task matches its description.

Can I use Videohub Story Editor 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 cacity/VideoHub --skill videohub-story-editor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/videohub-story-editor, .gemini/skills/videohub-story-editor, .github/skills/videohub-story-editor and .opencode/skills/videohub-story-editor in your project.

What does Videohub Story Editor need to run?

Going by SKILL.md and its folder, Videohub Story Editor needs Python for the scripts in its folder, the command-line tools its instructions call (python and npm) and credentials named DEEPSEEK_API_KEY, MINIMAX_API_KEY and DOUBAO_TTS_ACCESS_TOKEN. Our summary lists: Python 3; Node.js; A credential in DEEPSEEK_API_KEY; A credential in MINIMAX_API_KEY.

Does Videohub Story Editor access the network?

SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Videohub Story Editor safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Videohub Story Editor use?

Videohub Story Editor is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Videohub Story Editor use?

About 2.3k tokens (SKILL.md is roughly 9.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.2k tokens, read only when the agent opens those files.

What are the alternatives to Videohub Story Editor?

Skills that share tags, products or a category with Videohub Story Editor: Vox Explainer (CK42BB/vox-explainer-skill, 109 stars), Explain Video (limin112/min-skill, 454 stars), Qiaomu Cut (joeseesun/qiaomu-cut-skill, 372 stars) and Showtime (FavioVazquez/showtime, 220 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Videohub Story Editor?

cacity (a GitHub user) maintains it in cacity/VideoHub, which has 168 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on October 2, 2026.

Source: cacity/VideoHub on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.