Editor Ai Linkedin

professionals and marketers edit raw video footage into LinkedIn-ready videos using this skill. Accepts MP4, MOV, AVI, WebM up to 500MB, renders on cloud GPU...

Security Scan

The skill's declared purpose (cloud video editing) matches what the instructions do (call a remote nemovideo API using NEMO_TOKEN and upload video files), but there are a few minor inconsistencies and privacy/operational considerations you should review before installing.

Purpose & Capability

Name/description (LinkedIn video editing) align with runtime instructions: the SKILL.md describes uploading video files, creating a session, using render/export endpoints, and returning download URLs. Requesting a single API token (NEMO_TOKEN) is appropriate for this purpose.

Instruction Scope

Instructions explicitly direct the agent to POST video files and metadata to https://mega-api-prod.nemovideo.ai, create sessions, poll renders, and handle SSE streams — all expected for a cloud editor. The SKILL.md also instructs the agent to read this file's YAML frontmatter at runtime and to detect install path (~/.clawhub, ~/.cursor/skills) to set an attribution header; that requires read access to the skill file and possibly the agent's install paths. This is plausible but broader than strictly necessary for basic editing and is worth noting for privacy/least-privilege concerns.

Install Mechanism

Instruction-only skill with no install spec or code files — lowest install risk. Nothing is downloaded or written by an installer in the provided manifest.

Credentials

The skill declares a single required credential (NEMO_TOKEN), which matches the API calls in SKILL.md. However, SKILL.md metadata also references a config path (~/.config/nemovideo/) while the registry metadata earlier listed no required config paths — this is an inconsistency. The single token is proportionate, but the skill will upload user media to an external service (privacy/data exfiltration risk inherent to the described function).

Persistence & Privilege

always is false and the skill does not request permanent platform inclusion. It does instruct saving a session_id and the token for session use, which is normal for API-driven workflows and not an elevated privilege.

Scan Findings in Context

[no-code-files-scanned] expected: The static scanner found no code files to analyze because this is an instruction-only skill. That is expected for a SKILL.md-only integration; absence of findings is not proof of safety. Manual review of SKILL.md was used instead.

Assessment

This skill appears to do what it says: it uploads your video files to a nemovideo.ai API and returns edited exports, and it needs a single API token (NEMO_TOKEN). Before installing, confirm: (1) you trust the external domain (mega-api-prod.nemovideo.ai) to handle your videos and any PII — uploads occur off-device; (2) whether you’re comfortable the agent may read the skill file and detect install paths to set attribution headers; (3) the registry metadata mismatch about config paths (~/.config/nemovideo/) — ask the publisher why that path is referenced and whether any local files will be read. If any of these points are unacceptable, do not install or ask the publisher for documentation/security/privacy details and a verified homepage/source before proceeding.

Getting Started

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

Try saying:

• "edit my raw video footage"
• "export 1080p MP4"
• "trim pauses, add captions, and format"

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 LinkedIn Video Editor — Edit and Export LinkedIn Videos

Send me your raw video footage and describe the result you want. The AI LinkedIn video editing runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 90-second webcam recording of a professional update, type "trim pauses, add captions, and format for LinkedIn feed", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: keep clips under 3 minutes for best LinkedIn engagement and faster processing.

Matching Input to Actions

User prompts referencing editor ai linkedin, 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.

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

1. Session — POST /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. Upload — POST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
4. Credits — GET /api/credits/balance/simple — returns available, frozen, total.
5. State — GET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
6. Export — POST /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: editor-ai-linkedin
• 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)

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

• "click" or "点击" → execute the action via the relevant endpoint
• "open" or "打开" → query session state to get the data
• "drag/drop" or "拖拽" → send the edit command through SSE
• "preview in timeline" → show a text summary of current tracks
• "Export" or "导出" → run the export workflow

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.

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim pauses, add captions, and format for LinkedIn feed" — 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 LinkedIn and other platforms.

Common Workflows

Quick edit: Upload → "trim pauses, add captions, and format for LinkedIn feed" → 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.