Online Video Editor Ai

Tired of wrestling with complicated desktop software just to trim a clip or add a caption? online-video-editor-ai takes the friction out of video editing by...

Security Scan

The skill's requirements and runtime instructions align with a cloud-based video-editing agent: it only needs a single API token and makes network calls to the stated service, but minor metadata inconsistencies and the lack of a published source reduce confidence.

Purpose & Capability

The skill is an online video editor that uses a remote processing API; requesting a single service token (NEMO_TOKEN) and describing endpoints is coherent with that purpose. No unrelated cloud providers or unrelated credentials are requested.

Instruction Scope

SKILL.md instructs the agent to use NEMO_TOKEN (or obtain an anonymous token via a POST) and to create sessions, send SSE messages, upload local files, and request renders from mega-api-prod.nemovideo.ai. These actions are appropriate for remote video processing. The file references (upload paths) imply the agent may access user-supplied files; the doc also asks the agent to detect its install path for an X-Skill-Platform header. There is no instruction to read unrelated system files or unrelated env vars.

Install Mechanism

No install spec or external downloads — the skill is instruction-only, which is the lowest install risk.

Credentials

Only NEMO_TOKEN is required, which is proportional for an API-based editor. However, the SKILL.md frontmatter lists a configPaths entry (~/.config/nemovideo/) while the registry metadata shows none — this inconsistency could mean the agent may access a local config directory if implemented. The skill also describes creating an anonymous token via a network call and using it as NEMO_TOKEN (reasonable, but consider where that token is stored).

Persistence & Privilege

always is false and disable-model-invocation is false (normal). The skill does not request elevated or persistent platform-wide privileges and does not attempt to modify other skills' configs.

Assessment

This skill looks like a straightforward wrapper around a cloud video-processing API and asks only for a single API token (NEMO_TOKEN). Before installing: 1) confirm you trust the external domain (mega-api-prod.nemovideo.ai) because the skill will send video files and metadata there; 2) avoid placing highly sensitive files or unrelated credentials in uploads; 3) note the SKILL.md can generate an anonymous token if no token is provided — understand where that token will be stored and rotate it after use if you are unsure; 4) the frontmatter mentions a local config path (~/.config/nemovideo/) but the registry shows none — ask the publisher how that path is used or whether the skill will read local config files; and 5) because the skill has no published source or homepage, prefer running it in a sandboxed environment or request additional provenance information from the skill publisher before granting access to private files or long-lived credentials.

Getting Started

Welcome to your AI-powered video editing assistant — built to help you cut, caption, reformat, and polish videos without touching complicated software. Tell me what you're working on and let's get your video production-ready!

Try saying:

• "Trim my video to 60 seconds"
• "Write captions for product demo"
• "Reformat landscape video for TikTok"

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.

Edit Videos Smarter — Just Describe What You Need

Most video editing tools demand you already know what you're doing. Timelines, keyframes, export codecs — the learning curve alone can kill your momentum before you've made a single cut. online-video-editor-ai flips that experience entirely. Instead of hunting through menus, you describe your goal in plain language and get back actionable editing instructions, scripts, captions, and creative direction you can apply immediately.

Whether you're repurposing a long-form interview into punchy social clips, adding subtitles to a product demo, or figuring out the best pacing for a YouTube intro, this skill walks you through every decision with context-aware guidance. It understands the difference between a TikTok hook and a LinkedIn explainer — and tailors its suggestions accordingly.

This isn't a one-size-fits-all template generator. It responds to your specific footage description, target audience, platform requirements, and creative vision. Think of it as having an experienced video editor in the room who speaks plain English and never charges by the hour.

Routing Edits to the Right Pipeline

When you submit a prompt — whether it's a trim command, color grade request, subtitle burn-in, or AI scene cut — ClawHub parses the intent and routes it to the matching video processing endpoint automatically.

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 Rendering API Reference

All video operations run on a distributed cloud transcoding backend, meaning your timeline edits, AI enhancements, and export renders are processed server-side with no local GPU required. Requests are queued, encoded, and returned as streamable or downloadable output links via the API response payload.

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

• X-Skill-Source: online-video-editor-ai
• 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.

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)

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

Best Practices for Getting the Most Out of Online Video Editor AI

The more specific you are about your footage, the sharper the output. Instead of saying 'edit my video,' describe the content type (interview, tutorial, vlog, ad), the target platform (YouTube, Instagram Reels, LinkedIn), and the desired length or mood. This context lets the skill tailor its editing recommendations precisely rather than offering generic advice.

When requesting captions or scripts, always mention your audience. A B2B SaaS explainer needs different language than a fitness motivation reel — and the skill adjusts tone, pacing cues, and vocabulary accordingly.

If you're repurposing content across multiple platforms, tackle one format at a time. Ask for the YouTube version first, then request a separate pass optimized for vertical mobile viewing. Batching platform-specific requests separately produces cleaner, more targeted results than asking for everything at once.

Finally, treat the first response as a draft. Paste back the section you want refined and ask for alternatives — the skill iterates quickly and can offer multiple creative directions for intros, CTAs, or transition suggestions until one fits your vision.

Use Cases — Who Uses Online Video Editor AI and How

Content creators use online-video-editor-ai to break down long recordings into shareable clips, write timestamp descriptions for YouTube chapters, and generate hook scripts for the first five seconds of a Reel or Short — the make-or-break window for algorithm performance.

Marketing teams rely on it to repurpose webinar recordings into bite-sized social proof clips, draft lower-third text overlays for product videos, and align video pacing with ad campaign objectives. It's especially useful when a small team needs to produce high volumes of video content without a dedicated editor on staff.

Educators and course creators use it to structure tutorial scripts, suggest where to insert visual callouts or screen recording pauses, and generate accessible captions that match their teaching tone. It reduces the post-production bottleneck that often delays course launches.

Freelancers and agencies use it as a pre-edit planning tool — describing client footage and getting a proposed cut structure, B-roll placement suggestions, and music mood recommendations before opening their editing software. This saves hours of decision-making time on every project.