Video Skill Online

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

Security Scan

The skill's requirements and instructions are consistent with a remote video-editing service: it needs a single NEMO_TOKEN (or will obtain a short-lived anonymous token) and uploads user videos to the nemo backend — nothing else requested looks disproportionate.

Purpose & Capability

The name/description are aligned with the runtime instructions: the skill calls a remote video-editing API, uploads files, starts render jobs, checks credits/state, and returns download URLs. Requiring an API token (NEMO_TOKEN) is coherent with that purpose.

Instruction Scope

The SKILL.md explicitly instructs the agent to upload user video files and to call multiple endpoints on mega-api-prod.nemovideo.ai, obtain or use NEMO_TOKEN, start sessions, stream SSE, and poll render status. This is expected for a cloud editing service. Two items to note: (1) the skill will generate an anonymous token if NEMO_TOKEN is absent (POST to the auth endpoint), and (2) it reads the skill's YAML frontmatter and attempts to detect install path to set X-Skill-Platform — that requires reading the runtime/install path and possibly probing the home directory. No instructions ask for unrelated secrets or system-wide config beyond that.

Install Mechanism

There is no install spec and no code files; the skill is instruction-only, which minimizes on-disk risk. All runtime actions are remote API calls described in SKILL.md.

Credentials

Only one credential is declared: NEMO_TOKEN (primaryEnv). That is proportionate for an API-based service. Minor inconsistency: the SKILL.md frontmatter metadata mentions a config path (~/.config/nemovideo/) for discovery, but the registry metadata listed no required config paths — the difference is internal but worth noting because the skill may look in the user's config directory at runtime.

Persistence & Privilege

The skill is not marked always:true and does not request persistent system-wide privileges or modify other skills. It may read install path(s) and the user's config directory for attribution purposes, but it does not request elevated/system-wide access in its instructions.

Assessment

This skill appears to be what it claims: a cloud-based video editor that will upload your files to mega-api-prod.nemovideo.ai and requires an API token (NEMO_TOKEN) or will obtain a short-lived anonymous token on your behalf. Before installing/using it, consider: (1) Do you trust the nemo domain to receive and store your video content? (2) Only provide a dedicated NEMO_TOKEN (don’t reuse other sensitive service tokens). (3) The skill may read your install path and ~/.config/nemovideo/ if present — avoid sending sensitive footage or PII unless you accept remote processing and retention policies. If you need more assurance, request the service's privacy/security policy or a maintainer contact before uploading confidential content.

Getting Started

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

Try saying:

• "edit a 2-minute tutorial recording into a 1080p MP4"
• "trim the intro, add captions, and export for YouTube"
• "learning and applying video editing skills online for content creators"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

• Generate a UUID as client identifier
• POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
• The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Video Skill Online — Learn and Edit Videos Online

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

A quick example: upload a 2-minute tutorial recording, type "trim the intro, add captions, and export for YouTube", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 60 seconds process and preview faster during skill practice.

Matching Input to Actions

User prompts referencing video skill online, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint	Method	Purpose
/api/tasks/me/with-session/nemo_agent	POST	Start a new editing session. Body: {"task_name":"project","language":"<lang>"}. Returns session_id.
/run_sse	POST	Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/<sid>	POST	Upload a file (multipart) or URL.
/api/credits/balance/simple	GET	Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latest	GET	Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda	POST	Start export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

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

• X-Skill-Source: video-skill-online
• 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.

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

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.

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)

Common Workflows

Quick edit: Upload → "trim the intro, add captions, and export for YouTube" → Download MP4. Takes 1-2 minutes 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 the intro, add captions, and export for YouTube" — 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.