Video Trimmer In

Skip the learning curve of professional editing software. Describe what you want — trim the first 2 minutes and cut the silence at the end — and get trimmed...

Security Scan

The skill mostly matches its stated purpose (AI video trimming) and only needs a single service token, but there are small inconsistencies and scope decisions (automatic anonymous token creation and a mismatch over config paths) that warrant caution before installing.

Purpose & Capability

Name and description align with the required NEMO_TOKEN and the described cloud video-rendering API; requiring a single service token is proportionate. However, the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata listed no required config paths — this mismatch is unexplained.

Instruction Scope

Instructions stay within the declared remote service (mega-api-prod.nemovideo.ai) and define upload, SSE, session, export, and polling workflows. They instruct the agent to look for a local NEMO_TOKEN or automatically obtain one via an anonymous-token POST, and to upload user-supplied files by path. Automatic token creation and implicit filesystem access for uploads are reasonable for this skill but widen scope (network calls and local file reads) and should be disclosed to users.

Install Mechanism

No install spec and no code files (instruction-only) — lowest install risk. The skill does not download or write installer artifacts itself.

Credentials

The only declared credential is NEMO_TOKEN (primaryEnv), which fits the service. But the frontmatter's configPaths (~/.config/nemovideo/) suggests the skill may read or write a local config file (e.g., to persist tokens) even though registry metadata reported no required config paths. Also, the runtime behavior to auto-create an anonymous token (and treat it as NEMO_TOKEN) means the skill will perform network-auth operations and may persist credentials unless the storage location is clarified.

Persistence & Privilege

always:false and no instructions to modify other skills or system-wide agent settings. The skill requests no elevated platform privileges beyond normal network and file access for uploads and (possibly) storing its token locally.

What to consider before installing

This skill appears to do what it says (cloud AI trimming) and only asks for a single service token, but there are two things to confirm before installing: (1) consent for auto-creating an anonymous NEMO_TOKEN — the skill will POST to mega-api-prod.nemovideo.ai to obtain a token if none is supplied, which creates a 7‑day token and consumes free credits; if you prefer, provide your own NEMO_TOKEN instead of letting it create one; (2) whether the skill will read/write ~/.config/nemovideo/ (the SKILL.md frontmatter references this but the registry metadata did not) — ask the publisher where tokens/config are stored and whether they are persisted. Also avoid uploading sensitive or private videos unless you trust the nemo domain and have checked its privacy/retention policy.

Getting Started

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

Try saying:

• "edit my raw video footage"
• "export 1080p MP4"
• "trim the first 2 minutes and"

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 Trimmer In — Trim and Export Clean Videos

This tool takes your raw video footage and runs AI video trimming through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 10-minute interview recording and want to trim the first 2 minutes and cut the silence at the end — the backend processes it in about 20-40 seconds and hands you a 1080p MP4.

Tip: shorter source clips process faster and use fewer credits.

Matching Input to Actions

User prompts referencing video trimmer in, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header	Value
X-Skill-Source	video-trimmer-in
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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

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.

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.

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

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)

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim the first 2 minutes and cut the silence at the end" — 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 and devices.

Common Workflows

Quick edit: Upload → "trim the first 2 minutes and cut the silence at the end" → Download MP4. Takes 20-40 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.