Skill: dsewell-583h0/video-editing-with-linkedin (version 1.0.0)

--- name: video-editing-with-linkedin version: "1.0.0" displayName: "Video Editing with LinkedIn — Edit and Share LinkedIn Videos" description: > 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), describe what you need, and get 1080p MP4 output in 30-60 seconds. Built for marketers who work with video clips. metadata: {"openclaw": {"emoji": "💼", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "short_prompts"}} --- ## 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.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)