Video Editing With Linkedin

Cloud-based video-editing-with-linkedin tool that handles editing and formatting videos for LinkedIn posts. Upload MP4, MOV, AVI, WebM files (up to 500MB), d...

Security Scan

This skill is internally consistent with a cloud-based LinkedIn video editing service (it uploads user videos to nemovideo.ai and uses a NEMO_TOKEN), but it will send user media to an external backend so you should review privacy and trust of that service and a small metadata mismatch should be clarified.

Purpose & Capability

The name/description (cloud video editing for LinkedIn) matches the instructions: the skill uploads user video files and calls nemovideo.ai render endpoints. Requesting a NEMO_TOKEN is appropriate. Minor inconsistency: the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata reported 'required config paths: none' — clarify whether the skill will read that local config directory.

Instruction Scope

Runtime instructions are narrowly scoped to the nemovideo.ai API (session creation, SSE chat, upload, export, state, credits). The skill explicitly looks for NEMO_TOKEN in env and will otherwise obtain an anonymous token via the service's /api/auth/anonymous-token endpoint. It requires uploading user media to the external service (expected for cloud editing); no instructions reference unrelated files, other credentials, or broad system probing.

Install Mechanism

No install spec or code files are present (instruction-only), so nothing is downloaded or written to disk by an installer. This is the lower-risk model for skills that call external services.

Credentials

Only NEMO_TOKEN is declared as required/primary. The SKILL.md also documents a flow to obtain an anonymous token if none is present, which is consistent with the declared env var (it can use an existing token or create a short-lived anonymous one). There are no unrelated secret env vars requested.

Persistence & Privilege

The skill is not always-enabled and uses normal autonomous invocation settings. It asks the agent to hold a session_id for the duration of work but does not request system-wide config writes or other skills' credentials. No elevated privileges requested.

Assessment

This skill will upload any video files you provide to an external service at mega-api-prod.nemovideo.ai and use a NEMO_TOKEN (or obtain an anonymous token) to perform edits and return a downloadable MP4 — that behavior is coherent with the skill's purpose but does mean your media and any embedded data will leave your device. Before installing or using it, verify you trust nemovideo.ai (review its privacy/storage/retention policy), decide whether you prefer to supply your own NEMO_TOKEN versus allowing the skill to create an anonymous token, and ask the maintainer to clarify the config-path inconsistency in the frontmatter. If your videos contain sensitive information, avoid uploading them until you confirm how the service stores and processes content.

Getting Started

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

Try saying:

• "edit my video clips"
• "export 1080p MP4"
• "trim the video to 60 seconds"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

• Generate a UUID as client identifier
• POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
• Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Video Editing with LinkedIn — Edit and Share LinkedIn Videos

Drop your video clips in the chat and tell me what you need. I'll handle the LinkedIn video optimization on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 90-second interview recording, ask for trim the video to 60 seconds and add captions for LinkedIn autoplay, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — LinkedIn autoplays videos without sound, so adding captions significantly boosts engagement.

Matching Input to Actions

User prompts referencing video editing with 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.

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

Header	Value
X-Skill-Source	video-editing-with-linkedin
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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.

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)

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 Codes

• 0 — success, continue normally
• 1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token
• 1002 — session not found; create a new one
• 2001 — out of credits; anonymous users get a registration link with ?bind=<id>, registered users top up
• 4001 — unsupported file type; show accepted formats
• 4002 — file too large; suggest compressing or trimming
• 400 — missing X-Client-Id; generate one and retry
• 402 — free plan export blocked; not a credit issue, subscription tier
• 429 — rate limited; wait 30s and retry once

Common Workflows

Quick edit: Upload → "trim the video to 60 seconds and add captions for LinkedIn autoplay" → Download MP4. Takes 30-60 seconds 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim the video to 60 seconds and add captions for LinkedIn autoplay" — 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 full LinkedIn compatibility.