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mhogan2013-9

Video No Generator

by mhogan2013-9 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install video-no-generator
Description
Skip the learning curve of professional editing software. Describe what you want — remove the frame numbers or watermark numbers overlaid on my video — and g...
README (SKILL.md)

Getting Started

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

Try saying:

  • "remove my video clips"
  • "export 1080p MP4"
  • "remove the frame numbers or watermark"

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 No Generator — Remove Numbers From Videos

Drop your video clips in the chat and tell me what you need. I'll handle the video number removal on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute tutorial video with visible frame numbers, ask for remove the frame numbers or watermark numbers overlaid on my video, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips with static number positions process significantly faster.

Matching Input to Actions

User prompts referencing video no generator, 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-no-generator
  • 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 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)

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 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 "remove the frame numbers or watermark numbers overlaid on my video" — 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 frame numbers or watermark numbers overlaid on my video" → 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.

Usage Guidance
Before installing, make sure you are comfortable sending selected videos to nemovideo.ai and using or creating a Nemo token. For sensitive content or paid accounts, verify the provider, monitor credits, and ask for confirmation before export or other credit-consuming actions.
Capability Analysis
Type: OpenClaw Skill Name: video-no-generator Version: 1.0.0 The skill bundle is a functional integration for a video editing service hosted at mega-api-prod.nemovideo.ai. It provides structured instructions for an AI agent to manage authentication (including anonymous token acquisition), file uploads, and video processing tasks. While it requires access to a specific configuration path (~/.config/nemovideo/) and an environment variable (NEMO_TOKEN), these are consistent with its stated purpose of interfacing with the NemoVideo API, and no evidence of malicious intent or data exfiltration was found.
Capability Assessment
Purpose & Capability
The stated purpose—removing numbers or overlays from videos—matches the cloud video upload, edit, and export workflow. The skill also documents broader video-editing actions such as export, audio, and timeline state, so users should understand it is not purely local number removal.
Instruction Scope
Instructions route user requests and some backend responses into API actions. This is purpose-aligned for a cloud editor, but exports and edits should remain tied to the user's explicit request.
Install Mechanism
There is no install script or local code to execute. The main provenance gap is that the registry lists the source as unknown and no homepage, while the skill depends on a remote API.
Credentials
Using NEMO_TOKEN and uploading media to the provider are proportionate for this cloud-rendering purpose. Users should avoid uploading sensitive videos unless they trust the provider.
Persistence & Privilege
No local persistence, background process, or privilege escalation is shown. The skill does create provider-side sessions and render jobs, and anonymous tokens are described as valid for 7 days.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install video-no-generator
  3. After installation, invoke the skill by name or use /video-no-generator
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of Video No Generator v1.0.0. - Automatically removes overlaid frame numbers or watermark numbers from uploaded videos (MP4, MOV, AVI, WebM up to 500MB). - Simple upload and edit workflow, no manual editing needed; typical jobs complete in 30–60 seconds. - Seamless onboarding with automatic token retrieval and session setup. - Clear user prompts for uploading, editing, and exporting videos. - Supports batch and iterative editing with real-time cloud processing and status updates.
Metadata
Slug video-no-generator
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Video No Generator?

Skip the learning curve of professional editing software. Describe what you want — remove the frame numbers or watermark numbers overlaid on my video — and g... It is an AI Agent Skill for Claude Code / OpenClaw, with 41 downloads so far.

How do I install Video No Generator?

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

Is Video No Generator free?

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

Which platforms does Video No Generator support?

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

Who created Video No Generator?

It is built and maintained by mhogan2013-9 (@mhogan2013-9); the current version is v1.0.0.

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