Ai Video Editing Online

Cloud-based ai-video-editing-online tool that handles editing raw footage into polished videos without desktop software. Upload MP4, MOV, AVI, WebM files (up...

Security Scan

The skill's requests and runtime instructions are consistent with a cloud video-editing integration — it asks only for a single service token and instructs the agent to call a remote API — but there are minor metadata inconsistencies and a few implementation details you should confirm before using it with sensitive footage.

Purpose & Capability

The skill name/description (cloud AI video editing) matches the actions in SKILL.md: obtaining a NEMO_TOKEN, creating a session, uploading video files, streaming SSE edits, and requesting render jobs. All required capabilities (network calls, token-based auth, file uploads) are coherent with the stated purpose.

Instruction Scope

Instructions are narrowly scoped to interacting with the remote nemovideo API (auth, session creation, upload, SSE, render). They explicitly tell the agent not to print tokens/raw JSON. One minor scope note: headers include an X-Skill-Platform value that is derived from the agent's install path (~/.clawhub or ~/.cursor/skills/), which implies the agent may probe local paths to determine the platform — this is plausible for attribution but you should be aware it may require reading install paths.

Install Mechanism

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

Credentials

The skill requires a single service credential (NEMO_TOKEN), which is appropriate for a cloud-rendering service. Minor metadata inconsistency: SKILL.md metadata includes configPaths ("~/.config/nemovideo/"), but the registry summary listed no required config paths; clarify whether the agent will read that path and why. Otherwise no unrelated secrets are requested.

Persistence & Privilege

always:false and normal autonomous invocation. The skill asks to save a session_id for ongoing jobs (expected) but does not request elevated system-wide privileges or to modify other skills. No persistent installation behavior is declared.

Assessment

This skill appears to do what it claims: it will send uploaded video files and editing commands to the nemovideo cloud API and use a NEMO_TOKEN to authenticate. Before installing/using it: (1) confirm you trust the endpoint domain (mega-api-prod.nemovideo.ai) and review its privacy/retention policy for uploaded videos; (2) confirm whether the agent will store the anonymous token or NEMO_TOKEN persistently and where; (3) ask the skill author to clarify the metadata inconsistency about ~/.config/nemovideo/ (will the skill read that path?), and whether any local filesystem probing occurs to produce X-Skill-Platform headers; (4) avoid uploading sensitive or regulated footage until you verify the provider's handling and retention. Overall the skill is coherent with its purpose, but verify provider trust and token/storage behavior before sending private data.

Getting Started

Send me your raw video footage and I'll handle the AI video editing. Or just describe what you're after.

Try saying:

• "edit a 2-minute unedited screen recording into a 1080p MP4"
• "trim the silences, add transitions, and export as a clean MP4"
• "editing raw footage into polished videos without desktop software for content creators and marketers"

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 Video Editing Online — Edit and Export Videos Online

Send me your raw video footage 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 unedited screen recording, type "trim the silences, add transitions, and export as a clean MP4", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 3 minutes process significantly faster.

Matching Input to Actions

User prompts referencing ai video editing 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is ai-video-editing-online, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise 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 Codes

• 0 — success, continue normally
• 1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token
• 1002 — session not found; create a new one
• 2001 — out of credits; anonymous users get a registration link with ?bind=<id>, registered users top up
• 4001 — unsupported file type; show accepted formats
• 4002 — file too large; suggest compressing or trimming
• 400 — missing X-Client-Id; generate one and retry
• 402 — free plan export blocked; not a credit issue, subscription tier
• 429 — rate limited; wait 30s and retry 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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim the silences, add transitions, and export as a clean MP4" — 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 silences, add transitions, and export as a clean MP4" → 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.