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...

Security Scan

The skill's declared requirements and runtime instructions align with its stated purpose: it uses a NEMO API token to upload and render user video files on a third‑party cloud service; nothing requested looks disproportionate to that task.

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.

Scan Findings in Context

[static-scan-none] expected: No code files were present for static analysis; this is an instruction-only skill so the regex scanner had nothing to analyze. Absence of findings is expected in this context.

Assessment

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.

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: <uuid>. 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 <NEMO_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":"<lang>"} — returns task_id, session_id.

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

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

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

Session state: GET /api/state/nemo_agent/me/<sid>/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_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/<id> 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=<id> (get <id> 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.