Skill: mory128/login-video (version 1.0.0)

--- name: login-video version: "1.0.0" displayName: "Login Video — Create Login Walkthrough Videos Fast" description: > Turn a 30-second screen recording of an app login flow into 1080p polished login videos just by typing what you need. Whether it's creating onboarding or login tutorial videos for apps and websites or quick social content, drop your raw video footage and describe the result you want. No timeline dragging, no export settings — 30-60 seconds from upload to download. metadata: {"openclaw": {"emoji": "🔐", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "greeting_v2"}} --- ## Getting Started > Ready when you are. Drop your raw video footage here or describe what you want to make. **Try saying:** - "create a 30-second screen recording of an app login flow into a 1080p MP4" - "create a clean login walkthrough video with annotations and background music" - "creating onboarding or login tutorial videos for apps and websites for product teams, UX designers, marketers" ### 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. # Login Video — Create Login Walkthrough Videos Fast This tool takes your raw video footage and runs AI login video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result. Say you have a 30-second screen recording of an app login flow and want to create a clean login walkthrough video with annotations and background music — the backend processes it in about 30-60 seconds and hands you a 1080p MP4. Tip: keep your screen recording under 60 seconds for fastest processing and clearest output. ## Matching Input to Actions User prompts referencing login video, 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. Base URL: `https://mega-api-prod.nemovideo.ai` | Endpoint | Method | Purpose | |----------|--------|---------| | [REDACTED_SECRET] | POST | Start a new editing session. Body: `{"task_name":"project","language":"<lang>"}`. Returns `session_id`. | | `/run_sse` | POST | Send a user message. Body includes `app_name`, `session_id`, `new_message`. Stream response with `Accept: text/event-stream`. Timeout: 15 min. | | `/api/upload-video/nemo_agent/me/<sid>` | POST | Upload a file (multipart) or URL. | | `/api/credits/balance/simple` | GET | Check remaining credits (`available`, `frozen`, `total`). | | `/api/state/nemo_agent/me/<sid>/latest` | GET | Fetch current timeline state (`draft`, `video_infos`, `generated_media`). | | `/api/render/proxy/lambda` | POST | Start export. Body: `{"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}`. Poll status every 30s. | Accepted file types: 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`: `login-video` - `X-Skill-Version`: from frontmatter `version` - `X-Skill-Platform`: detect from install path (`~/.clawhub/` → `clawhub`, `~/.cursor/skills/` → `cursor`, else `unknown`) Include `Authorization: Bearer <NEMO_TOKEN>` and all attribution headers on every request — omitting them triggers a 402 on export. ### 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 ### 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. ### 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 **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) ``` ## Common Workflows **Quick edit**: Upload → "create a clean login walkthrough video with annotations and background music" → 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 "create a clean login walkthrough video with annotations and background music" — 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 widest compatibility across web and mobile platforms.


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