Video Trimmer By

Get trimmed video clips ready to post, without touching a single slider. Upload your video clips (MP4, MOV, AVI, WebM, up to 500MB), say something like "trim...

Security Scan

The skill's declared requirements and runtime instructions are coherent with a cloud-based video trimming service; nothing requests unrelated credentials or intrusive system access, though there are small metadata inconsistencies to be aware of.

Purpose & Capability

The skill is a cloud video-trimming frontend and only requires a service token (NEMO_TOKEN) and API calls to nemovideo.ai, which matches the stated purpose. The SKILL.md also documents an anonymous-token flow if NEMO_TOKEN is not present, which is a reasonable convenience. Minor inconsistency: the registry listed no config paths but the SKILL.md frontmatter references ~/.config/nemovideo/.

Instruction Scope

Instructions focus on uploading video, posting edit messages (SSE), polling render status, and returning download URLs. They instruct detecting install path and reading this file's frontmatter for attribution headers; that means the agent may read its own skill file and check a few well-known paths. The instructions do not ask for unrelated files, system credentials, or broad data collection beyond uploaded videos and session tokens.

Install Mechanism

No install spec or third-party packages — instruction-only skill (lowest install risk). Nothing will be downloaded or written by an installer step.

Credentials

Only NEMO_TOKEN (primaryEnv) is requested, which is proportional for a cloud API. However, the skill both declares NEMO_TOKEN as required and documents an anonymous-token POST flow when NEMO_TOKEN is not set; this metadata mismatch is sloppy but not malicious. The frontmatter's configPaths hint at potentially reading ~/.config/nemovideo/ (possible token or config storage), which could be justified for persistence but should be explicit in registry metadata.

Persistence & Privilege

always is false and the skill does not request elevated or persistent platform-wide privileges. It stores a session_id for API interaction (normal) and does not instruct modifying other skills or system-wide configs.

Assessment

This skill appears to do what it says: it uploads video to nemovideo.ai, requests edits, and returns a download URL. Before installing, consider: (1) You will be sending your video content to https://mega-api-prod.nemovideo.ai — ensure you trust that service for privacy/confidentiality. (2) The registry metadata and the SKILL.md disagree slightly (required config path vs none, and declaring NEMO_TOKEN required while providing an anonymous-token flow). That looks like sloppy metadata rather than malice, but you may want to supply your own NEMO_TOKEN if you prefer control over authentication. (3) The skill may read its own SKILL.md and check a few well-known install/config paths (e.g., ~/.config/nemovideo/, ~/.clawhub/) to populate attribution headers — if you are uncomfortable with any local path checks, ask the author to make these explicit or remove them. (4) No installers or unrelated credentials are requested, which reduces risk. If you need higher assurance, verify the nemovideo.ai domain and their privacy policy, and avoid sending sensitive footage until you confirm their data retention and access policies.

Getting Started

Send me your video clips and I'll handle the AI video trimming. Or just describe what you're after.

Try saying:

• "edit a 10-minute interview recording into a 1080p MP4"
• "trim the first 2 minutes and cut the last 30 seconds of silence"
• "cutting and trimming video footage to exact length for content creators"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Video Trimmer By NemoVideo — Trim and Export Video Clips

This tool takes your video clips 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 last 30 seconds of silence — the backend processes it in about 20-40 seconds and hands you a 1080p MP4.

Tip: shorter source clips process faster and give more precise trim points.

Matching Input to Actions

User prompts referencing video trimmer by, 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: video-trimmer-by
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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.

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 last 30 seconds of silence" — 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.

Common Workflows

Quick edit: Upload → "trim the first 2 minutes and cut the last 30 seconds of silence" → 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.