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Video Narration Ai

作者 mhogan2013-9 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ pending
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在 OpenClaw 中安装
/install video-narration-ai
功能描述
Skip the learning curve of professional editing software. Describe what you want — add a voiceover narration that describes what's happening on screen — and...
使用说明 (SKILL.md)

Getting Started

Got video clips to work with? Send it over and tell me what you need — I'll take care of the AI narration generation.

Try saying:

  • "add a 2-minute product demo video into a 1080p MP4"
  • "add a voiceover narration that describes what's happening on screen"
  • "adding AI voiceover narration to silent or music-only videos for content creators"

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: \x3Cuuid>. 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.

Video Narration AI — Add AI Voiceover to Videos

Send me your video clips and describe the result you want. The AI narration generation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 2-minute product demo video, type "add a voiceover narration that describes what's happening on screen", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: shorter clips under 3 minutes produce the most accurate and natural-sounding narration.

Matching Input to Actions

User prompts referencing video narration ai, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says... Action Skip 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

Cloud Render Pipeline Details

Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"\x3Clang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/\x3Csid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/\x3Csid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s for completed status and download URL.

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

Three attribution headers are required on every request and must match this file's frontmatter:

Header Value
X-Skill-Source video-narration-ai
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

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

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

  • "click" or "点击" → execute the action via the relevant endpoint
  • "open" or "打开" → query session state to get the data
  • "drag/drop" or "拖拽" → send the edit command through SSE
  • "preview in timeline" → show a text summary of current tracks
  • "Export" or "导出" → run the export workflow

SSE Event Handling

Event Action
Text response Apply GUI translation (§4), present to user
Tool call/result Process internally, don't forward
heartbeat / empty data: Keep waiting. Every 2 min: "⏳ Still working..."
Stream closes Process 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.

Error Codes

  • 0 — success, continue normally
  • 1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token
  • 1002 — session not found; create a new one
  • 2001 — out of credits; anonymous users get a registration link with ?bind=\x3Cid>, registered users top up
  • 4001 — unsupported file type; show accepted formats
  • 4002 — file too large; suggest compressing or trimming
  • 400 — missing X-Client-Id; generate one and retry
  • 402 — free plan export blocked; not a credit issue, subscription tier
  • 429 — rate limited; wait 30s and retry once

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "add a voiceover narration that describes what's happening on screen" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.

Export as MP4 for widest compatibility across platforms and devices.

Common Workflows

Quick edit: Upload → "add a voiceover narration that describes what's happening on screen" → Download MP4. Takes 30-60 seconds for a 30-second clip.

Batch style: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.

Iterative: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.

如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install video-narration-ai
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /video-narration-ai 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Video Narration AI 1.0.0 — Initial Release - Instantly add AI-powered voiceover narration to uploaded video files (MP4, MOV, AVI, WebM, up to 500MB) - Simple workflow: upload video, describe your desired narration, and receive a narrated video in 30–60 seconds - Cloud-based GPU rendering—no installation or editing software required - Automatic session and token management; supports free usage credits via anonymous API tokens - Export narrated videos in MP4 and other common formats with quick download - Handles narration for short video clips (<3 minutes) with optimal quality for content creators
元数据
Slug video-narration-ai
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Video Narration Ai 是什么?

Skip the learning curve of professional editing software. Describe what you want — add a voiceover narration that describes what's happening on screen — and... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 31 次。

如何安装 Video Narration Ai?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install video-narration-ai」即可一键安装,无需额外配置。

Video Narration Ai 是免费的吗?

是的,Video Narration Ai 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Video Narration Ai 支持哪些平台?

Video Narration Ai 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Video Narration Ai?

由 mhogan2013-9(@mhogan2013-9)开发并维护,当前版本 v1.0.0。

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