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vidnoz-ai-music-video-generatorvidnoz ai 音乐视频生成器

Agent Skill

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。

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OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:vidnoz-ai-music-video-generator(vidnoz ai 音乐视频生成器)
来源仓库:https://github.com/linmillsd7/vidnoz-ai-music-video-generator
安装命令:
openclaw skills install vidnoz-ai-music-video-generator
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install vidnoz-ai-music-video-generator

简介

自动将原始剪辑与音轨合成为节拍同步的音乐视频。

  • 无需手动编辑,支持场景传输与动态视觉匹配算法。
  • 适合音乐推广、社交媒体传播与品牌宣传片制作。vidnoz-ai-music-video-generator 属于音频生成类 Skill,可作为该场景下的辅助能力补充。
  • 注意音轨版权归属,建议使用原创或授权背景音乐。
  • 通过 clawhub 安装并接入 OpenClaw 音频视觉创作流程。

SKILL.md

name
vidnoz-ai-music-video-generator
version
1.0.0
displayName
Vidnoz AI Music Video Generator — Sync Footage to Music Automatically
description
>
metadata
{"openclaw": {"emoji": "🎬", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "short_prompts"}}

Getting Started

Welcome! You've got footage and a track — let's turn them into something worth sharing. Tell me what you're working with and I'll help you build a beat-synced music video using Vidnoz AI right now.

Try saying:

  • "Sync my clips to this track"
  • "Create a 30-second music reel"
  • "Match cuts to beat drops"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Create Beat-Synced Music Videos in Minutes

Making a music video used to mean hours in a timeline editor, manually cutting clips to match every beat drop and melody shift. The Vidnoz AI Music Video Generator changes that entirely. By analyzing both your footage and your audio track simultaneously, it identifies rhythm patterns, tempo changes, and emotional peaks — then assembles your clips to match them naturally.

This skill gives you direct access to that automation layer. You can describe the style you want, specify the mood, select transition types, or let the AI make creative decisions based on your source material. Whether you're producing a lyric video, a brand reel, a wedding highlight, or a social media clip, the output is timed, coherent, and visually engaging.

The tool is designed for people who want quality results without needing professional editing experience. You bring the footage and the song — the AI brings the timing, the cuts, and the visual flow. It's a practical shortcut from raw media to shareable video.

Routing Clips and Beat Requests

When you submit a footage upload or music sync request, ClawHub parses your intent and routes it to the appropriate Vidnoz AI pipeline — whether that's beat detection, auto-cut sequencing, or transition styling.

User says...ActionSkip SSE?
"export" / "导出" / "download" / "send me the video"→ §3.5 Export
"credits" / "积分" / "balance" / "余额"→ §3.3 Credits
"status" / "状态" / "show tracks"→ §3.4 State
"upload" / "上传" / user sends file→ §3.2 Upload
Everything else (generate, edit, add BGM…)→ §3.1 SSE

Vidnoz Cloud Processing Reference

Vidnoz AI handles all music-to-video synchronization server-side, using its beat-matching engine to analyze BPM, waveform peaks, and rhythm patterns before applying automated cuts and transitions to your footage. Your rendered music video is processed entirely in the cloud, so local hardware specs have no impact on export quality or sync accuracy.

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source: vidnoz-ai-music-video-generator
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

All requests must include: Authorization: Bearer <NEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"<lang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/<sid> — file: multipart -F "files=@/path", or URL: {"urls":["<url>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/<sid>/latest — key fields: data.state.draft, data.state.video_infos, data.state.generated_media

Export (free, no credits): POST /api/render/proxy/lambda — body {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/<id> every 30s until status = completed. Download URL at output.url.

Supported formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

SSE Event Handling

EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultProcess internally, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess final response

~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend saysYou do
"click [button]" / "点击"Execute via API
"open [panel]" / "打开"Query session state
"drag/drop" / "拖拽"Send edit via SSE
"preview in timeline"Show track summary
"Export button" / "导出"Execute export workflow

Draft field mapping: t=tracks, tt=track type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

Error Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

Performance Notes

The vidnoz-ai-music-video-generator performs best when your audio track has a clear, consistent tempo or identifiable beat markers. Songs with strong percussion or defined drops give the AI more anchor points for cut alignment, resulting in tighter sync.

For footage, shorter clips (3–10 seconds each) tend to produce more dynamic results than long uncut takes. The more variety in your source material — different angles, movement speeds, and lighting — the more visually interesting the final edit will be.

If you're working with a track that has a slow tempo or ambient structure, specify a 'mood-based' rather than 'beat-based' sync mode. This tells the AI to prioritize emotional pacing over strict rhythmic cuts, which suits cinematic and documentary-style videos far better.

Common Workflows

Most users approach the vidnoz-ai-music-video-generator with one of three workflows. The first is the full-auto approach: upload footage and audio, let the AI select clip order, transition style, and beat alignment without manual input. This works well for social content where speed matters more than precise creative control.

The second workflow is style-guided generation. Here you describe a visual mood — cinematic, energetic, minimal, nostalgic — and the AI applies matching effects, color treatment, and cut pacing to your material. This is popular for brand videos and music artist content.

The third workflow is segment-specific editing: you lock certain scenes to specific timestamps in the song and let the AI fill the gaps. This gives you creative checkpoints while still automating the bulk of the assembly. It's the preferred method for wedding films and narrative-driven reels where specific moments must hit on cue.

Use Cases

The vidnoz-ai-music-video-generator fits a wide range of real-world content needs. Musicians and bands use it to produce lyric videos and visual albums without hiring a video editor. The AI handles the timing and aesthetics while the artist focuses on the creative direction.

Social media managers use it to turn product footage into scroll-stopping reels timed to trending audio, dramatically cutting production time per post. E-commerce brands find it especially useful for seasonal campaigns where multiple product videos need to be produced quickly.

Event videographers — particularly in weddings and corporate productions — rely on it to deliver highlight reels the same day as the event. And independent content creators on YouTube and TikTok use it to add a professional polish to vlogs and travel content without investing in expensive software or editing skills.

适合场景

01

生成背景音乐

02

生成歌曲或旋律

03

视频和播客配乐

04

社媒内容音频素材

能力概览

能力 1

调用音乐生成模型

能力 2

支持文本到音乐或歌曲生成

能力 3

提供 CLI 示例和使用场景

能力 4

适合音频内容工作流

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

92.36%
按下载量换算820

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

敏感数据

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