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Video Explanation

作者 peandrover adam · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install video-explanation
功能描述
Get explained video content ready to post, without touching a single slider. Upload your existing video file (MP4, MOV, AVI, WebM, up to 500MB), say somethin...
使用说明 (SKILL.md)

Getting Started

Share your existing video file and I'll get started on AI explanation generation. Or just tell me what you're thinking.

Try saying:

  • "generate my existing video file"
  • "export 1080p MP4"
  • "explain what is happening in this"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

  • Generate a UUID as client identifier
  • POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
  • The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Video Explanation — Generate explanations from videos

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

A quick example: upload a 3-minute product demo video, type "explain what is happening in this video step by step", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: shorter clips under 2 minutes produce more focused and accurate explanations.

Matching Input to Actions

User prompts referencing video explanation, 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.

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

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

All requests must include: Authorization: Bearer \x3CNEMO_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":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

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

Session state: GET /api/state/nemo_agent/me/\x3Csid>/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_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> 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

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.

Backend Response Translation

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

Backend says You 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 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 "explain what is happening in this video step by step" — 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.

Common Workflows

Quick edit: Upload → "explain what is happening in this video step by step" → 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.

安全使用建议
Install/use this skill only if you are comfortable sending selected video files to NemoVideo’s cloud service. Use a dedicated token if available, avoid sensitive media unless you trust the provider, and ask for confirmation before exports or edits when working with important content.
功能分析
Type: OpenClaw Skill Name: video-explanation Version: 1.0.0 The video-explanation skill is a legitimate integration for the nemovideo.ai API, designed to automate video analysis and rendering. It provides clear instructions for session management, file uploads, and credit tracking using standard HTTP requests to https://mega-api-prod.nemovideo.ai. The skill's requirement for an environment variable (NEMO_TOKEN) and a local config path (~/.config/nemovideo/) is consistent with its stated purpose, and no evidence of data exfiltration, malicious execution, or harmful prompt injection was found.
能力评估
Purpose & Capability
The requested capabilities match the stated purpose: upload a user-provided video, process it on remote GPU nodes, and export an MP4. The main user-facing risk is that media leaves the local machine for cloud processing.
Instruction Scope
The skill routes user intents and some backend GUI-like responses into API actions such as upload, state checks, and export. This is purpose-aligned, but users should supervise the workflow for sensitive or valuable videos.
Install Mechanism
There is no install script or code execution artifact, which lowers local execution risk. Provenance is limited because the source is listed as unknown and there is no homepage.
Credentials
The skill requires or obtains a NemoVideo token and makes network calls to the disclosed NemoVideo API. That is proportionate for a cloud rendering integration.
Persistence & Privilege
The artifacts describe remote sessions, render job IDs, and an anonymous token valid for 7 days, but do not show local background persistence or hidden privilege escalation.
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-explanation
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /video-explanation 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
- Initial release of "Video Explanation — Generate explanations from videos" skill. - Enables users to upload video files (MP4, MOV, AVI, WebM up to 500MB) and generate step-by-step AI-driven video explanations with 1080p MP4 export. - Easy setup: automatic token handling, backend connection, and simple status messaging ("Connecting...", "Ready"). - Supports key actions via prompt and file upload: generate explanations, export video, check credits, and session state. - All rendering and processing occur in the cloud; no local installation required. - Robust error handling and user guidance for file formats, size, credits, and session management.
元数据
Slug video-explanation
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 Explanation 是什么?

Get explained video content ready to post, without touching a single slider. Upload your existing video file (MP4, MOV, AVI, WebM, up to 500MB), say somethin... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 42 次。

如何安装 Video Explanation?

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

Video Explanation 是免费的吗?

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

Video Explanation 支持哪些平台?

Video Explanation 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 Explanation?

由 peandrover adam(@peand-rover)开发并维护,当前版本 v1.0.0。

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