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Agent Skill · 前端设计

realistic-ugc-video(逼真的 UGC 视频)

用于辅助视频生成、动画合成、脚本化剪辑或 Remotion 等视频项目开发。它适合让 Agent 组织镜头、生成素材说明、维护合成代码或排查渲染问题。使用时需要确认分辨率、时长、素材路径和导出格式;涉及外部素材、人物肖像或商业发布时,应先核对版权授权和内容审核要求。

realistic-ugc-video 是前端设计类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描有未通过项,按安装量在前端设计类的 10,216 个 Skill 里排第 2,055。

总安装 2,982周安装 123GitHub Stars 5下载 974核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:realistic-ugc-video(逼真的 UGC 视频)
来源仓库:https://github.com/dennisonbertram/claude-media-skills
仓库路径:skills/realistic-ugc-video
安装命令:
npx skills add https://github.com/dennisonbertram/claude-media-skills --skill realistic-ugc-video
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/dennisonbertram/claude-media-skills --skill realistic-ugc-video

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

用于用户生成内容的视频制作与脚本编写。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。支持镜头规划、素材说明和 Remotion 合成代码生成。可协助排查渲染问题并控制输出分辨率及时长。涉及人物肖像或商用素材时须确认版权许可。

realistic-ugc-video 属于前端设计类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/realistic-ugc-video

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/dennisonbertram/claude-media-skills --skill re…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

realistic-ugc-video 怎么安装?

在终端执行 npx skills add https://github.com/dennisonbertram/claude-media-skills --skill realistic-ug…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

realistic-ugc-video 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

realistic-ugc-video 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/dennisonbertram/claude-media-skills --skill realistic-ugc-video 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

realistic-ugc-video 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

realistic-ugc-video 用的人多吗?

公开数据是累计安装 2,982 次,近一周安装 123 次,下载 974 次,GitHub 5 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

realistic-ugc-video 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理前端设计类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
realistic-ugc-video

逼真的 UGC 视频 · 本页

2,9825执行命令未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Realistic UGC Video Production

Create long-form AI videos that look and sound authentically human. This skill orchestrates a multi-step workflow using Nano Banana for realistic base images and Kling AI for video generation, with specific techniques to avoid the "AI look".

Why Videos Look AI (And How to Fix It)

ProblemSolution
Too perfect/clean skinAdd imperfections: micro-pores, natural oils, fine lines
Studio lightingUse available/natural light, mixed color temps
Character too stillAdd micro-movements, head tilts, natural sway
Inconsistent pacingUse 55-60 syllables per clip
Robotic voiceProcess through Adobe Podcast or Resemble AI
Obvious jump cutsCover with B-roll or animations
Weird AI handsCrop hands out of frame or keep completely static

Known Limitation: Hands

AI video models (Kling, Veo, etc.) struggle with realistic hand movement. Fingers morph, gestures look unnatural, and hands are often the biggest tell.

Best practice: Keep hands OUT of frame or completely static.

Options:

  1. Head/shoulders framing - Crop base image to exclude hands entirely
  2. Arms crossed - Static pose, no finger movement needed
  3. Hands below frame - Desk edge cuts off at wrists
  4. Cover with B-roll - Cut away during any hand weirdness in post

Complete Workflow

Phase 1: Collect Requirements

Before starting, gather from the user:

  1. Character description - Age, ethnicity, features, clothing
  2. Setting/background - Office, home, studio, outdoor
  3. Script - The full text the character will speak
  4. Tone - Conversational, urgent, professional, friendly
  5. Video length target - This determines how many clips needed

Phase 2: Generate Base Image (Nano Banana)

Use the Nano Banana skill to generate the character image. Critical: Apply the imperfection techniques from CHARACTER-PROMPTING.md.

Key elements for realistic UGC:

  • iPhone capture aesthetic (26mm equivalent lens)
  • Available/mixed lighting (NOT studio)
  • Visible skin texture (pores, oils, fine lines)
  • Minor imperfections (stubble, dark circles)
  • Computational depth artifacts
  • ISO noise (500-900 range)

Command:

~/.claude/skills/nano-banana/scripts/generate.sh "[enhanced prompt]" --aspect 9:16 --size 2K

Then optionally upscale through Enhancor AI for additional texture.

Phase 3: Chunk the Script (Critical for Pacing)

This is the most important step for natural pacing. See SCRIPT-CHUNKING.md.

The 55-60 Syllable Rule:

  • Count syllables, not words
  • Each video generation = 55-60 syllables
  • Never cut mid-sentence
  • Add filler sentences to reach target if needed

Example chunking:

Chunk 1 (58 syllables):
"Hey everyone, I wanted to share something that completely changed how I think about productivity. It's not another app or system."

Chunk 2 (56 syllables):
"It's actually about understanding your own energy patterns throughout the day. Once I figured this out, everything clicked into place."

Phase 4: Generate Video Clips (Kling AI)

For each script chunk, generate a 10-second video clip. Use the Kling AI skill with movement prompts from MOVEMENT-PROMPTING.md.

Key elements:

  • Hand "Home Base" Protocol
  • Timestamped movement clusters
  • Natural blinks, head tilts, micro-sways
  • Consistent base image reference

Spawn background agent for each clip:

Task tool:
- subagent_type: "general-purpose"
- run_in_background: true
- prompt: [Include image URL, script chunk, movement prompt, output path]

Phase 5: Post-Production

See POST-PRODUCTION.md for detailed guidance.

  1. Assemble clips in CapCut or similar editor
  2. Fix audio with Adobe Podcast (minimum) or Resemble AI (for voice swap)
  3. Cover jump cuts with B-roll or animations
  4. Remove filler sentences if they feel awkward
  5. Export in final resolution

Quick Start: Single Clip Test

Before generating full video, test the workflow with one clip:

  1. Generate base image with full imperfections
  2. Create 10-second test video with first script chunk
  3. Evaluate pacing and movement
  4. Adjust prompts if needed
  5. Proceed with full production

Example Full Prompt for Base Image

A vertical 9:16 UGC-style video frame captured on an iPhone 11 resting on a tripod.
Medium-wide portrait at true eye-level with slightly forward-leaning posture.

[CHARACTER]: A [age] [gender] with [ethnicity] complexion, [eye color] eyes beneath
[eyebrow description], [nose description]. [Jawline/facial hair]. [Hair description].
Expression is [emotion]—[specific expression details].

[CLOTHING]: [Fitted/casual garment], [collar detail].

[SKIN TEXTURE]: Visible pores across T-zone, faint smile lines, natural oils catching
light on forehead and nose. [Age-appropriate details]. No filter, no foundation.

[FOREGROUND]: Hands rest naturally on [surface], fingers relaxed, visible veins and
knuckle texture. Nearby: [everyday objects like water bottle, phone, notebook].

[CAMERA]: Native iPhone 11 lens (26mm equivalent), slightly wide perspective, mild
barrel softness at edges. Only tiny pockets of neural blur around hair edges.

[LIGHTING]: Available light mix—cool overcast daylight from window left, warm tungsten
from desk lamp right. Soft asymmetric shadows, natural falloff. ISO noise 500-900.

[BACKGROUND]: [Realistic home/office elements]—bookshelf, [furniture], clearly visible
not heavily blurred.

[REALITY DETAILS]: Gentle 35mm film grain, light fingerprint smudge on lens, tiny dust
haze in air. No cinematic bloom, no studio finish.

Styling: raw UGC realism, available indoor light, mixed color temperature, minimal
depth blur, visible ISO noise, emphasis on authenticity.

Example Movement Prompt for Video

Hand "Home Base" Protocol: Hands default to Active Idle. Fingers shift, thumbs rub,
wrists rotate slightly while anchored. Gestures only for key emphasis.

[0.0s-0.5s] Pre-roll: Sharp inhale, eyes lock to lens, head still
[0.5s-3.0s] Hands in Active Idle (fingers interlocked), head tilts slightly right,
           brows furrow in seriousness
[3.0s-6.0s] Hands break clasp for quick open-palm rotation then return, head drifts
           forward, natural blink
[6.0s-8.0s] Hands return to Active Idle (loose clasp, thumbs tapping), head nods
           encouragingly, cheeks lift in natural smile
[8.0s-10.0s] Hands anchored (wrist shifts), chin lifts in quick final nod, natural blink

[Script]: "[CHUNK TEXT HERE]"
[Tone]: [Urgent/Conversational/Professional/etc.]
[Pacing]: Rapid fire delivery, high energy, viral UGC style, confident, 2x speed

Reference Files

Alternative: InfiniteTalk

For simpler long-form videos, consider InfiniteTalk (infinitetalk.ai).

Pros: Single generation for longer videos Cons: Less control over pacing (no timer/duration control), charged by output length

Use the syllable method above when precise pacing control is needed.

Checklist Before Generating

  • Character prompt includes skin imperfections
  • Lighting is available/natural, NOT studio
  • Script chunked into 55-60 syllable segments
  • Each chunk is complete sentences
  • Movement prompt includes hand base, head movements, blinks
  • Post-production plan for audio and jump cuts

平台分布

Codex

34.15%
按下载量换算333

Claude

30.13%
按下载量换算293

Cursor

17.2%
按下载量换算168

Gemini CLI

9.46%
按下载量换算92

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/dennisonbertram/claude-media-skills --skill realistic-ugc-video 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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