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tk8544-b

Ai Product Video Cutter

by tk8544-b · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install ai-product-video-cutter
Description
Get trimmed product clips ready to post, without touching a single slider. Upload your raw product footage (MP4, MOV, AVI, WebM, up to 500MB), say something...
README (SKILL.md)

Getting Started

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

Try saying:

  • "cut my raw product footage"
  • "export 1080p MP4"
  • "cut the best 30-second highlight clips"

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.

AI Product Video Cutter — Cut Product Videos into Clips

Drop your raw product footage in the chat and tell me what you need. I'll handle the AI video cutting on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 3-minute product demo recording, ask for cut the best 30-second highlight clips from my product 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 — keeping source clips under 2 minutes gives the AI more precise cut points.

Matching Input to Actions

User prompts referencing ai product video cutter, 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 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.

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

  • X-Skill-Source: ai-product-video-cutter
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

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.

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

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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut the best 30-second highlight clips from my product 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 across ad platforms and social media.

Common Workflows

Quick edit: Upload → "cut the best 30-second highlight clips from my product 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
This skill will upload any video you send to a third-party service (mega-api-prod.nemovideo.ai) and uses a NEMO API token (or an anonymous token the skill can request) to operate. Before installing or using it, consider: (1) Do you trust the service and owner to process and store your videos? Avoid uploading sensitive or private footage unless you accept that it will leave your device. (2) The skill can create and store a short-lived anonymous token (100 credits, 7 days) — treat NEMO_TOKEN like a secret and do not paste it into public logs. (3) The skill may read small local metadata (this file's frontmatter and install path) to populate attribution headers; if you need to restrict filesystem access, run in a sandbox. (4) If you need stronger privacy guarantees, ask the vendor for retention and deletion policies or process media locally with trusted tooling instead.
Capability Analysis
Type: OpenClaw Skill Name: ai-product-video-cutter Version: 1.0.0 The skill 'ai-product-video-cutter' is a functional integration for the Nemo Video AI service, providing detailed instructions in SKILL.md for an agent to process videos via the mega-api-prod.nemovideo.ai API. It includes standard procedures for session management, file uploads, and automated anonymous token generation if a NEMO_TOKEN is not provided. While it performs platform detection to set attribution headers, all behaviors are transparently documented and strictly aligned with the stated purpose of video editing without any indicators of malicious intent or data exfiltration.
Capability Assessment
Purpose & Capability
The skill is a cloud-based video cutting service and only requests a single API credential (NEMO_TOKEN) and an optional config path (~/.config/nemovideo/) consistent with a client for that service. Required binaries and install steps are absent, which matches an instruction-only cloud-integrator skill.
Instruction Scope
Runtime instructions focus on authenticating (optional anonymous token endpoint), creating a session, uploading videos (multipart or URL), starting render jobs, polling status, and downloading results. The instructions explicitly tell the agent not to print tokens. They also instruct the agent to read this file's YAML frontmatter and to detect its install path (to set X-Skill-Platform) — reading those local metadata/paths is plausible but not strictly necessary for core functionality and will require the agent to inspect its runtime environment.
Install Mechanism
No install spec or downloadable artifacts are present; this is instruction-only, so nothing is written to disk by an installer. That is the lowest-risk installation footprint.
Credentials
Only one credential (NEMO_TOKEN) is required and it is the primary credential needed to call the indicated API endpoints. The manifest's configPaths entry (~/.config/nemovideo/) could grant access to local config but is consistent with a client that might store tokens or settings there. No unrelated secrets or multiple external credentials are requested.
Persistence & Privilege
The skill is not forced-always, and autonomous invocation is allowed by platform default. It does not request elevated or cross-skill configuration changes. There is no install-time modification of other skills or persistent privileged presence.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install ai-product-video-cutter
  3. After installation, invoke the skill by name or use /ai-product-video-cutter
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
ai-product-video-cutter v1.0.0 - Initial release: Instantly cut e-commerce product videos into highlight clips using AI—no manual editing needed. - Upload raw product footage (MP4, MOV, AVI, WebM, up to 500MB). - Simple workflow: upload, request highlight clips (e.g., "cut the best 30-second highlight clips"), and download 1080p MP4 output in about a minute. - No installation required; processing runs on cloud GPUs. - Designed for fast-moving e-commerce marketers needing quick, hands-off video trimming.
Metadata
Slug ai-product-video-cutter
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Ai Product Video Cutter?

Get trimmed product clips ready to post, without touching a single slider. Upload your raw product footage (MP4, MOV, AVI, WebM, up to 500MB), say something... It is an AI Agent Skill for Claude Code / OpenClaw, with 122 downloads so far.

How do I install Ai Product Video Cutter?

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

Is Ai Product Video Cutter free?

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

Which platforms does Ai Product Video Cutter support?

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

Who created Ai Product Video Cutter?

It is built and maintained by tk8544-b (@tk8544-b); the current version is v1.0.0.

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