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dsewell-583h0

Video Ai No

by dsewell-583h0 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install video-ai-no
Description
Get cleaned video files ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something like...
README (SKILL.md)

Getting Started

Share your raw video footage and I'll get started on AI video removal. Or just tell me what you're thinking.

Try saying:

  • "remove my raw video footage"
  • "export 1080p MP4"
  • "remove the person in the background"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

  • Generate a UUID as client identifier
  • POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
  • Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Video AI No — Remove Elements from Videos

Send me your raw video footage and describe the result you want. The AI video removal runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 2-minute interview clip with unwanted background objects, type "remove the person in the background from my video automatically", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 30 seconds process significantly faster and more accurately.

Matching Input to Actions

User prompts referencing video ai no, 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.

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

  • X-Skill-Source: video-ai-no
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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)

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

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 Handling

Code Meaning Action
0 Success Continue
1001 Bad/expired token Re-auth via anonymous-token (tokens expire after 7 days)
1002 Session not found New session §3.0
2001 No credits Anonymous: show registration URL with ?bind=\x3Cid> (get \x3Cid> from create-session or state response when needed). Registered: "Top up credits in your account"
4001 Unsupported file Show supported formats
4002 File too large Suggest compress/trim
400 Missing X-Client-Id Generate Client-Id and retry (see §1)
402 Free plan export blocked Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429 Rate limit (1 token/client/7 days) Retry in 30s once

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "remove the person in the background from my video automatically" — 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 → "remove the person in the background from my video automatically" → Download MP4. Takes 1-2 minutes 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.

Usage Guidance
This skill appears purpose-aligned for cloud video cleanup. Before installing, make sure you are comfortable sending raw video files to the NemoVideo backend, using or creating a NEMO_TOKEN session, and allowing the agent to run export/edit workflows through that service.
Capability Analysis
Type: OpenClaw Skill Name: video-ai-no Version: 1.0.0 The skill bundle provides instructions for an AI agent to interface with a video processing service at nemovideo.ai. It includes standard procedures for authentication (anonymous token generation), session management, and file handling (upload/export) via REST APIs. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found; the logic is consistent with the stated purpose of AI-assisted video editing.
Capability Assessment
Purpose & Capability
The visible instructions align with the stated purpose of cloud-based video cleanup and export. The skill also describes broader video-editing actions like BGM, overlays, and audio tracks, but these remain within a video-editing workflow.
Instruction Scope
The skill instructs the agent to translate backend GUI-like responses into API actions, including export workflows. This appears purpose-aligned, but users should watch for credit-consuming or state-changing actions.
Install Mechanism
There is no install script or code to execute, which limits local execution risk. The source is listed as unknown and no homepage is provided, so users have limited provenance information for the cloud service.
Credentials
Use of NEMO_TOKEN and NemoVideo API calls is proportional to the cloud-rendering purpose, and the artifact says not to expose tokens or raw API output.
Persistence & Privilege
The skill keeps a session_id for operations and uses short-lived anonymous tokens; visible artifacts do not show local persistence beyond the declared NemoVideo configuration path, but cloud jobs may continue if the tab is closed.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install video-ai-no
  3. After installation, invoke the skill by name or use /video-ai-no
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of Video AI No — Remove Elements from Videos. - Upload raw video files (up to 500MB), give AI editing instructions, and download cleaned 1080p MP4 videos. - Fully automated setup: connects to the cloud backend, checks for tokens, and manages sessions for you. - Supports fast object/person removal without manual editing or sliders. - Handles multiple common workflows: quick edits, batch processing, and iterative refinement. - Includes clear error handling, supported formats, and tips for optimal results.
Metadata
Slug video-ai-no
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Video Ai No?

Get cleaned video files ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something like... It is an AI Agent Skill for Claude Code / OpenClaw, with 32 downloads so far.

How do I install Video Ai No?

Run "/install video-ai-no" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Video Ai No free?

Yes, Video Ai No is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Video Ai No support?

Video Ai No is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Video Ai No?

It is built and maintained by dsewell-583h0 (@dsewell-583h0); the current version is v1.0.0.

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