Skill flagged — suspicious patterns detected

ClawHub Security flagged this skill as suspicious. Review the scan results before using.

Youtube Video Editor Job

v1.0.0

Get polished YouTube videos ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something...

0· 119·0 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 linmillsd7/youtube-video-editor-job.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Youtube Video Editor Job" (linmillsd7/youtube-video-editor-job) from ClawHub.
Skill page: https://clawhub.ai/linmillsd7/youtube-video-editor-job
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 youtube-video-editor-job

ClawHub CLI

Package manager switcher

npx clawhub@latest install youtube-video-editor-job
Security Scan
VirusTotalVirusTotal
Pending
View report →
OpenClawOpenClaw
Suspicious
medium confidence
Purpose & Capability
Name/description match the runtime instructions: the skill uploads user video files to nemo's cloud API and requests a NEMO_TOKEN for Bearer auth. Requiring a token and calling nemovideo.ai endpoints is proportionate to the stated video-editing purpose.
Instruction Scope
SKILL.md instructs the agent to use NEMO_TOKEN or obtain an anonymous token by POSTing to nemovideo.ai and to upload files via multipart/form-data (files=@/path). Those actions fit the stated purpose. However, the frontmatter metadata also references a config path (~/.config/nemovideo/) and an instruction to auto-detect install path for X-Skill-Platform, which implies the agent may read local paths/installation context — this is not explained in the prose and expands scope beyond simple upload/API calls.
Install Mechanism
Instruction-only skill with no install steps and no code files. No downloads or archives are requested, so there is no install-time execution risk.
!
Credentials
The only declared env var is NEMO_TOKEN (primaryEnv), which is reasonable for a cloud API. But the SKILL.md frontmatter lists a configPaths entry (~/.config/nemovideo/). The registry metadata presented earlier did not list config paths — this inconsistency is concerning because access to a user config directory could expose additional secrets or tokens not mentioned in the public requirements.
Persistence & Privilege
always is false and the skill does not request persistent/always-on presence or modify other skills. Autonomous invocation is allowed (default) but not combined with other high-risk flags.
What to consider before installing
This skill appears to do what it says (upload video to nemo cloud and return edits) and only asks for a single token (NEMO_TOKEN). Before installing, consider: (1) Do not put sensitive credentials into NEMO_TOKEN unless you trust nemo‑video.ai and the skill author. (2) Ask the author to clarify the frontmatter configPaths entry (~/.config/nemovideo/) — confirm whether the skill will read that directory and why. (3) If you don't want the skill to use any existing local nemo config, run it without NEMO_TOKEN so it uses an anonymous token (note: anonymous tokens may have rate/expiry limits). (4) Only upload footage you are comfortable sending to an external service. If you need higher assurance, request the skill owner provide a privacy/security statement or an audited implementation. If the author cannot justify reading local config paths, treat that as a red flag and avoid installing.

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

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk971rpqsd0r98ged11h818mybn859f74
119downloads
0stars
1versions
Updated 1w 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 dead air, 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.

YouTube Video Editor — Edit and Export YouTube Videos

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

Say you have a 10-minute unedited vlog recording and want to cut dead air, add transitions, and export for YouTube upload — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 5 minutes process significantly faster.

Matching Input to Actions

User prompts referencing youtube video editor job, 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.

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

Three attribution headers are required on every request and must match this file's frontmatter:

HeaderValue
X-Skill-Sourceyoutube-video-editor-job
X-Skill-Versionfrontmatter version
X-Skill-Platformauto-detect: clawhub / cursor / unknown from install path

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.

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

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

SSE Event Handling

EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultProcess internally, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess 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.

Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

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 "cut dead air, add transitions, and export for YouTube upload" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for best YouTube compatibility.

Common Workflows

Quick edit: Upload → "cut dead air, add transitions, and export for YouTube upload" → 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.

Comments

Loading comments...