Editor Ai Youtube

v1.0.0

YouTubers edit raw video footage into edited YouTube videos using this skill. Accepts MP4, MOV, AVI, WebM up to 500MB, renders on cloud GPUs at 1080p, and re...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for francemichaell-15/editor-ai-youtube.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Editor Ai Youtube" (francemichaell-15/editor-ai-youtube) from ClawHub.
Skill page: https://clawhub.ai/francemichaell-15/editor-ai-youtube
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 editor-ai-youtube

ClawHub CLI

Package manager switcher

npx clawhub@latest install editor-ai-youtube
Security Scan
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OpenClawOpenClaw
Benign
high confidence
Purpose & Capability
Name/description describe a cloud AI video editor and the SKILL.md only requests an API token (NEMO_TOKEN) and describes API calls to a rendering backend (mega-api-prod.nemovideo.ai), which is proportionate to the stated purpose.
Instruction Scope
Instructions focus on establishing a session, uploading video files, streaming SSE messages, polling export status, and returning download URLs — all appropriate for a cloud editor. They explicitly instruct obtaining an anonymous token if no NEMO_TOKEN is present and to upload files (multipart or via URL). Note: SKILL.md references detecting install path (~/.clawhub, ~/.cursor/skills/) and a config path (~/.config/nemovideo/) in frontmatter metadata; the instructions do not clearly justify reading the user's filesystem beyond receiving user-supplied upload paths, so this is a small ambiguity to verify.
Install Mechanism
Instruction-only skill with no install spec and no code files, so nothing is written to disk by an installer. This is low risk from an install perspective.
Credentials
Only NEMO_TOKEN is declared as required and used. That token is the expected credential for a hosted service. The skill instructs creating a short-lived anonymous token if none is present, which is consistent with the service flow.
Persistence & Privilege
always is false and there is no request for persistent system-wide privileges or modification of other skills. The skill is eligible for autonomous invocation (platform default) but does not request elevated installation privileges.
Assessment
This skill appears internally consistent for a cloud video editor, but before installing consider the following: (1) Using the skill uploads your raw video to mega-api-prod.nemovideo.ai — do you trust that endpoint and its privacy/retention policies? (2) The skill accepts a NEMO_TOKEN; prefer using a short-lived or anonymous token rather than a long-lived personal secret. (3) SKILL.md mentions a config path (~/.config/nemovideo/) and infers install-path-based headers — clarify whether the skill will read those local paths if you care about filesystem privacy. (4) Because this is instruction-only (no code files), static scanners had nothing to analyze; runtime behavior (network calls, file uploads) happens when the skill runs, so limit use with sensitive content unless you verify the vendor. (5) If you need stronger assurance, request the skill publisher or vendor homepage, privacy policy, and a list of exactly which headers/metadata are transmitted with uploads.

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

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk9743z50tw27rb94aqfffbsyrh84kr97
94downloads
0stars
1versions
Updated 2w ago
v1.0.0
MIT-0

Getting Started

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

Try saying:

  • "edit my raw video footage"
  • "export 1080p MP4"
  • "cut out silences, add transitions, and"

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.

AI Editor for YouTube — Edit and Export YouTube Videos

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 10-minute unedited YouTube vlog, type "cut out silences, add transitions, and export as a YouTube-ready video", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 5 minutes process significantly faster.

Matching Input to Actions

User prompts referencing editor ai youtube, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is editor-ai-youtube, 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).

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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.

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

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

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 "cut out silences, add transitions, and export as a YouTube-ready video" — 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 YouTube and other platforms.

Common Workflows

Quick edit: Upload → "cut out silences, add transitions, and export as a YouTube-ready video" → 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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