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Clipping Video

by peandrover adam · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install clipping-video
Description
Get trimmed video clips ready to post, without touching a single slider. Upload your raw footage (MP4, MOV, AVI, WebM, up to 500MB), say something like "cut...
README (SKILL.md)

Getting Started

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

Try saying:

  • "trim my raw footage"
  • "export 1080p MP4"
  • "cut this down to the best"

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.

Clipping Video — Trim and Export Video Clips

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

A quick example: upload a 10-minute interview recording, type "cut this down to the best 60-second highlight clip", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: shorter source videos process faster and yield cleaner cuts.

Matching Input to Actions

User prompts referencing clipping video, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is clipping-video, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).

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.

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)

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 "cut this down to the best 60-second highlight clip" — 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.

Common Workflows

Quick edit: Upload → "cut this down to the best 60-second highlight clip" → 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
Install or use this skill only if you are comfortable uploading your footage to https://mega-api-prod.nemovideo.ai. Keep NEMO_TOKEN private, monitor credits and render status, and avoid uploading sensitive videos unless you trust the provider's privacy and retention practices.
Capability Analysis
Type: OpenClaw Skill Name: clipping-video Version: 1.0.0 The skill is a legitimate integration for a cloud-based video editing service hosted at nemovideo.ai. It manages authentication via anonymous tokens, handles session creation, and facilitates video uploads and processing on remote GPU nodes as described in SKILL.md. All network activity and file handling are consistent with the stated purpose of trimming and exporting video clips.
Capability Assessment
Purpose & Capability
The purpose is coherent and disclosed: SKILL.md says users upload raw footage and that "AI clip trimming runs on remote GPU nodes" with server-side rendering. Users should still treat uploaded media as data shared with a cloud provider.
Instruction Scope
The instructions automatically set up a backend connection on first use and then route upload, edit, export, credit, and status actions to the NemoVideo API; this is purpose-aligned but should be visible to the user.
Install Mechanism
There is no install spec and no code files, reducing local execution risk. The registry also lists Source as unknown and Homepage as none, so provider provenance cannot be verified from the supplied artifacts.
Credentials
The skill requires or creates a service-specific NEMO_TOKEN and uses it as a Bearer token for the declared video-processing backend; no unrelated credential use is shown.
Persistence & Privilege
The skill keeps a session_id for operations, uses anonymous tokens with a stated 7-day expiry, and notes that cloud render jobs may become orphaned if the tab closes before completion.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install clipping-video
  3. After installation, invoke the skill by name or use /clipping-video
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
**Initial release: Trim, highlight, and export video clips without manual editing.** - Instantly trim video footage with AI—simply upload and describe the result you want. - Cloud processing: No local installs needed; supports MP4, MOV, AVI, and WebM up to 500MB. - Guided setup automatically connects to backend and manages tokens for you. - Simple commands for upload, export, credits check, and timeline previews. - Fast 1080p MP4 exports, with most jobs done in under a minute. - Handles multiple tracks (video, audio, text overlays); session keeps editing state for iterative refinements.
Metadata
Slug clipping-video
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Clipping Video?

Get trimmed video clips ready to post, without touching a single slider. Upload your raw footage (MP4, MOV, AVI, WebM, up to 500MB), say something like "cut... It is an AI Agent Skill for Claude Code / OpenClaw, with 66 downloads so far.

How do I install Clipping Video?

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

Is Clipping Video free?

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

Which platforms does Clipping Video support?

Clipping Video is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Clipping Video?

It is built and maintained by peandrover adam (@peand-rover); the current version is v1.0.0.

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