Trimmer In Between

edit video clips into trimmed joined clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for removing unwanted m...

Security Scan

The skill's requests and runtime instructions are largely consistent with a cloud-based video trimming service, but there are a few small mismatches and privacy considerations you should be aware of before using it.

Purpose & Capability

The skill claims to trim/join videos via a cloud backend and all declared endpoints, headers, and workflows match that purpose. Minor incoherence: requires.env declares NEMO_TOKEN as a required credential yet the runtime instructions include an anonymous-token flow to obtain a NEMO_TOKEN automatically if one is not present.

Instruction Scope

Instructions tell the agent to upload user video files and metadata to https://mega-api-prod.nemovideo.ai and to poll session/render endpoints — this is expected for a cloud render service but is effectively sending user content off-device. The skill also instructs reading local install paths and this file's YAML frontmatter at runtime to populate attribution headers (reads ~/.clawhub/, ~/.cursor/skills/, and the SKILL.md file). Those file reads are not strictly necessary for trimming and leak some environment information; they increase the scope of data the agent accesses.

Install Mechanism

Instruction-only skill with no install spec and no code files — nothing is written to disk by an installer. This is the lowest install risk profile.

Credentials

Only one credential is declared (NEMO_TOKEN) which is proportional for a remote API. However, the skill's instructions will obtain an anonymous token automatically if none is present, which makes the 'required' designation ambiguous. There are no unrelated credentials requested.

Persistence & Privilege

always is false and the skill is not requesting elevated or persistent platform privileges. It does state that session tokens and job IDs exist server-side (normal for a render service), but it does not request modifying other skills or system-wide settings.

Assessment

This skill appears to be a straightforward cloud-based video trimmer: it will upload your videos and associated metadata to mega-api-prod.nemovideo.ai for processing and will use a NEMO_TOKEN (either one you set or one obtained anonymously). Consider the following before installing/using: (1) Privacy — your videos are sent to a third party; check their retention/terms if the content is sensitive. (2) Credential behavior — if you don't set NEMO_TOKEN yourself, the skill will call an anonymous-token endpoint and use that token (7-day expiry, free credits) — decide whether you prefer to supply your own token. (3) Local reads — the skill will probe a couple of install-path locations and read this SKILL.md frontmatter to build attribution headers; this is low-risk but unnecessary for trimming. (4) Source/maintainer — there is no homepage or source repo listed; if you need higher assurance, ask the publisher for a repo, privacy policy, or official docs before using. If you want the assessment to change: provide the skill's source code or an official homepage/maintainer contact and details about what data the backend retains/how it is protected.

Getting Started

Ready when you are. Drop your video clips here or describe what you want to make.

Try saying:

• "edit a 3-minute interview with unwanted middle section into a 1080p MP4"
• "trim out the section between 0:45 and 1:30 and join the remaining clips seamlessly"
• "removing unwanted middle segments from video clips for content creators"

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.

Trimmer In Between — Cut and Join Video Segments

Send me your video clips and describe the result you want. The AI segment trimming runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 3-minute interview with unwanted middle section, type "trim out the section between 0:45 and 1:30 and join the remaining clips seamlessly", and you'll get a 1080p MP4 back in roughly 20-40 seconds. All rendering happens server-side.

Worth noting: mark your in and out points precisely before trimming to avoid re-renders.

Matching Input to Actions

User prompts referencing trimmer in between, 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.

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

• X-Skill-Source: trimmer-in-between
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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.

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

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

Common Workflows

Quick edit: Upload → "trim out the section between 0:45 and 1:30 and join the remaining clips seamlessly" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim out the section between 0:45 and 1:30 and join the remaining clips seamlessly" — 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.