Vox 视频风格制作

SKILL前端设计
前端设计 未标注权限 许可证不明确
安装这个技能

为定稿口播生成 8 种可选 Vox 视频风格的分镜、时间轴、即梦图片提示词与 Google Omni 图生视频提示词。

一句话选型结论

按资料字段整理

Vox 视频风格制作是前端设计类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类前端设计 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_f0300397/vox-video-style-production
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

前端设计
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_f0300397仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 1791732201
正文体量8.4 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
出页面与组件

按描述生成页面结构和组件草稿。

调整样式与布局

改间距、配色与响应式布局。

生成设计说明

把设计稿整理成开发能接的说明。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在前端设计场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
Vox 视频风格制作当前 未标注权限 未标注 未标注 未标注 有
前端设计 只读 GitHub 仓库 882.3 万 Codex、Claude、Cursor 有
Vercel 组合模式 联网访问 GitHub 仓库 385.9 万 Codex、Claude、Cursor 有
Vercel React native skills 前端 只读 GitHub 仓库 246.9 万 Codex、Claude、Cursor 有
adapt 搜索 浏览器控制 GitHub 仓库 202.7 万 Codex、Claude、Cursor 有
使用我的浏览器 浏览器控制 GitHub 仓库 184.8 万 Codex、Claude、Cursor 有

SKILL.md 全文

8.4 KB
模型实际读到的说明书原文,来自技能仓库

Vox Video Style Production

Turn locked narration into a complete, internally consistent production pack. Preserve the narration exactly. Plan visuals, timing, image generation, and image-to-video motion without generating media.

Load the rules

Read these files before producing the pack:

  • styles.yaml as the single source of truth for style selection, the default style, Jimeng style prompts, Google Omni motion prompts, and style-specific negative prompts.
  • timing-and-storyboard.md for duration estimates, beat splitting, continuity, and factual restraint.
  • visual-dna.md for style-neutral composition, recurring-subject rules, labels, and motion constraints.
  • output-contract.md for required artifacts, fields, prompt assembly, and final checks.

Read user-guide.zh-CN.md or user-guide.en.md only when the user asks how to invoke, configure, customize, troubleshoot, or distribute this skill.

Never hardcode, paraphrase, or maintain a second copy of any style prompt outside config/styles.yaml.

Defaults

Apply these defaults unless the user explicitly overrides them:

  • Input: finalized narration, not a topic, outline, or draft.
  • Platform: Douyin.
  • Duration boundary: under 3 minutes.
  • Canvas: 16:9 landscape, 1920 x 1080 planning resolution.
  • Visual style: the style referenced by default_style in config/styles.yaml.
  • Image target: Jimeng.
  • Image-to-video target: Google Omni.
  • Generated source clip: 10 seconds per image; the edit may use only the shot's planned timeline duration.
  • Camera: locked unless the selected style's motion configuration explicitly calls for a restrained fixed-frame treatment.
  • Output language: match the user's language. Keep prompts in detailed Chinese by default.

Workflow

1. Validate the narration

Treat the supplied narration as locked copy. Do not rewrite, shorten, embellish, fact-correct, reorder, or add voiceover words unless the user separately asks for copy editing.

Estimate runtime. Label it as an estimate when no audio or word-level timestamps are available. If the estimate exceeds 180 seconds, report the excess before generating the full pack and ask whether to keep the full script or return for trimming. Never silently remove narration.

2. Resolve one visual style

Load config/styles.yaml. Match an explicit user choice against the numeric key, id, name_zh, or aliases. Select exactly one style.

If the user gives no style, use default_style and state the selected number and name in the production summary. If the value is invalid or ambiguous, display the eight numbered name_zh values in config order and ask one concise selection question. Do not blend styles unless a future config explicitly enables that behavior.

Use the selected style record for the whole video. Copy image_prompt_zh into every Jimeng prompt, video_motion_prompt_zh into every Google Omni prompt, and negative_prompt_zh into both where applicable. Never substitute motifs from an unselected style.

3. Build the continuity lock

Extract recurring people, objects, locations, documents, vehicles, dates, maps, and color signals. Assign each recurring subject one reusable description. Copy that wording unchanged into every prompt where the subject recurs.

Distinguish confirmed facts from visual inference. Never invent a face, uniform, weapon, document wording, date, number, or location detail and present it as factual. For unidentified or sensitive real people, prefer rear view, silhouette, cropped hands, obscuration, or a censor treatment compatible with the selected style.

4. Split the narration into beats

Split at sentence or natural clause boundaries. Give each beat one visual idea and normally 2.0 to 3.2 seconds of narration, matching the target range in timing-and-storyboard.md. Preserve every narration character and keep the original order.

Compute cumulative estimated timecodes using timing-and-storyboard.md. Do not create gaps or overlaps. Make the final end time equal the total estimate.

5. Direct each shot

Convert the core idea of each beat into one strong documentary visual. Do not illustrate every noun. Select one hero element at roughly 70 percent of visual weight, no more than three supporting elements, and generous negative space.

Choose a style-neutral composition grammar from visual-dna.md. Avoid using the same grammar for more than two consecutive beats. Express every grammar through the selected style only.

6. Write the Jimeng prompts

Write one complete, standalone Jimeng prompt per beat. Include the scene, locked recurring-subject wording, composition, camera framing, label allowance, the selected image_prompt_zh verbatim, aspect ratio, quality target, and selected negative_prompt_zh. Never refer to another prompt or say "same style as above".

Permit no text by default. Allow one 1-to-4-word label only when a name, date, location, or number is narratively essential. Spell the exact permitted label inside the prompt.

7. Write the Google Omni prompts

Write one complete, standalone image-to-video prompt per beat. Treat the supplied Jimeng image as the finished reference composition. Preserve identities, labels, framing, scale, colors, layer order, and object count.

Include the selected video_motion_prompt_zh verbatim, then add shot-specific choreography, opening state, reveal order, final hold, camera lock, ambient sound, and selected negative_prompt_zh. Keep narration and music out of generated clips.

8. Deliver and audit

Follow output-contract.md. For short results, return the whole pack in the response. For long results, create the three required files in a writable workspace and link them. Do not truncate prompts, replace them with examples, or omit later shots.

Run the mechanical half of the audit with the bundled checker, which needs only Python 3.10 or newer and no third-party packages:

python scripts/check_pack.py --storyboard <topic>-storyboard.md --jimeng <topic>-jimeng-prompts.txt --omni <topic>-google-omni-prompts.md --narration <narration file> --style <selected style>

It prints one JSON object and exits non-zero when anything fails, naming the offending shot numbers. It verifies the style resolves to exactly one record, the timeline is contiguous from zero, the narration survives verbatim and in order, one Jimeng and one Omni prompt exist per shot, every prompt carries the selected image_prompt_zh / video_motion_prompt_zh / negative_prompt_zh, no unselected style's prompt leaked in, no prompt refers to another, every Jimeng prompt states 16:9, and no em dash appears anywhere. Fix what it reports and re-run before delivering; when the pack is returned in the response rather than as files, write the three artifacts to a temporary location and check them there.

The checker measures; it does not judge. Confirm the remaining contract items yourself:

  • Every prompt contains the selected config blocks and no unselected style motifs.
  • Recurring subjects use identical locked wording.
  • No prompt requests gore, victim suffering close-ups, logos, watermarks, or unapproved text.

Scope boundaries

Do not generate video ideas, rewrite the narration, synthesize voiceover, create thumbnails, generate images, or render video unless the user explicitly expands the request. This skill's default deliverable is the production plan and prompt pack only.

常见问题

5 问
答案由本站依据条目字段整理
Vox 视频风格制作怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_f0300397/vox-video-style-production。安装方式为未标注。装完刷新技能列表或重开客户端。

Vox 视频风格制作支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

Vox 视频风格制作权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

Vox 视频风格制作收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

Vox 视频风格制作用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。