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Vn Video Editor

v1.0.0

Turn a 2-minute smartphone-recorded vlog clip into 1080p edited video clips just by typing what you need. Whether it's editing and enhancing short-form socia...

0· 45·0 current·0 all-time

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for vcarolxhberger/vn-video-editor.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Vn Video Editor" (vcarolxhberger/vn-video-editor) from ClawHub.
Skill page: https://clawhub.ai/vcarolxhberger/vn-video-editor
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: NEMO_TOKEN
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install vn-video-editor

ClawHub CLI

Package manager switcher

npx clawhub@latest install vn-video-editor
Security Scan
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medium confidence
Purpose & Capability
The name/description, required NEMO_TOKEN, and the SKILL.md’s API endpoints are coherent for a cloud video-editing service: uploading video, queuing renders, and returning a download URL. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) that is not declared in the registry metadata — that mismatch is unexpected and should be explained by the publisher.
Instruction Scope
Instructions are explicit: obtain or use NEMO_TOKEN (including deriving one via an anonymous-token endpoint), create a session, upload files, stream SSE edits, poll export status, and return download URLs. The skill will upload user media and persist a session_id. It also requires reading its own frontmatter to populate attribution headers and suggests inspecting install paths to detect platform. There is no instruction to read unrelated user files or shell history, but the upload of user videos to an external domain is central and requires explicit user consent.
Install Mechanism
Instruction-only skill with no install spec or code files — nothing will be written to disk by an installer. This is the lowest install risk.
!
Credentials
The single required credential (NEMO_TOKEN) is appropriate for a cloud editing service. However, the SKILL.md frontmatter claims an additional config path (~/.config/nemovideo/) while the registry metadata lists none. That discrepancy means the runtime instructions may expect filesystem access not declared in registry requirements. Also note that NEMO_TOKEN grants access to the remote account/service and will be sent with every API call; only provide a long-lived token if you trust the endpoint. The skill also instructs creating and storing temporary anonymous tokens if no token is present.
Persistence & Privilege
always:false and default agent invocation are appropriate. The skill stores a session_id and uses tokens for API calls, but it does not request permanent 'always' presence or attempt to modify other skills or global settings.
What to consider before installing
This skill will upload your video files to https://mega-api-prod.nemovideo.ai and uses a NEMO_TOKEN for authorization. Before installing or supplying credentials: verify the service and publisher provenance (homepage/owner info are missing here), confirm the privacy/retention policy for uploaded media, and prefer using a short-lived/anonymous token rather than a persistent account token. Ask the publisher to explain the registry/frontmatter mismatch (the SKILL.md references ~/.config/nemovideo/ and install-path checks but the registry metadata does not). If you don't trust the endpoint or can't confirm who runs it, avoid providing a long-lived NEMO_TOKEN and do not upload sensitive videos.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk9789f03qs8mnv8hxnj7ey8s8h85kjaz
45downloads
0stars
1versions
Updated 2d ago
v1.0.0
MIT-0

Getting Started

Share your raw video clips and I'll get started on AI video editing. Or just tell me what you're thinking.

Try saying:

  • "edit my raw video clips"
  • "export 1080p MP4"
  • "trim the footage, add music, and"

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.

VN Video Editor — Edit and Export Polished Videos

This tool takes your raw video clips and runs AI video editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 2-minute smartphone-recorded vlog clip and want to trim the footage, add music, and apply color grading — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing vn video editor, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip 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.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> every 30s for completed status and download URL.

Formats: 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: vn-video-editor
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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)

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend saysYou 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

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.

Error Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate 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 footage, add music, and apply color grading" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, AVI, MKV for the smoothest experience.

Export as MP4 with H.264 codec for widest compatibility across platforms.

Common Workflows

Quick edit: Upload → "trim the footage, add music, and apply color grading" → 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.

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