Skill: mhogan2013-9/video-bootcamp (version 1.0.0)

--- name: video-bootcamp version: "1.0.0" displayName: "Video Bootcamp — Edit and Export Training Videos" description: > Get polished training videos ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something like "cut dead air, add chapter titles, and export a clean training video", and download 1080p MP4 when it's done. Built for course creators and online trainers who move fast and want to produce professional training videos without advanced editing skills. metadata: {"openclaw": {"emoji": "🎬", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "greeting_v2"}} --- ## Getting Started > Send me your raw video footage and I'll handle the AI video editing. Or just describe what you're after. **Try saying:** - "edit a 10-minute unedited screen recording of a tutorial session into a 1080p MP4" - "cut dead air, add chapter titles, and export a clean training video" - "turning raw session recordings into structured video course lessons for course creators and online trainers" ### First-Time Connection When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up..."). **Authentication**: Check if `NEMO_TOKEN` is set in the environment. If it is, skip to step 2. 1. **Obtain a free token**: Generate a random UUID as client identifier. POST to `https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token` with header `X-Client-Id` set to that UUID. The response `data.token` is your NEMO_TOKEN — 100 free credits, valid 7 days. 2. **Create a session**: POST to `https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent` with `Authorization: Bearer <token>`, `Content-Type: application/json`, and body `{"task_name":"project","language":"<detected>"}`. Store the returned `session_id` for all subsequent requests. Keep setup communication brief. Don't display raw API responses or token values to the user. # Video Bootcamp — Edit and Export Training Videos Drop your raw video footage in the chat and tell me what you need. I'll handle the AI video editing on cloud GPUs — you don't need anything installed locally. Here's a typical use: you send a a 10-minute unedited screen recording of a tutorial session, ask for cut dead air, add chapter titles, and export a clean training video, and about 1-3 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default. One thing worth knowing — breaking your bootcamp into short 5-10 minute segments speeds up processing and keeps learners engaged. ## Matching Input to Actions User prompts referencing video bootcamp, 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. Headers are derived from this file's YAML frontmatter. `X-Skill-Source` is `video-bootcamp`, `X-Skill-Version` comes from the `version` field, and `X-Skill-Platform` is detected from the install path (`~/.clawhub/` = `clawhub`, `~/.cursor/skills/` = `cursor`, otherwise `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 | ## Common Workflows **Quick edit**: Upload → "cut dead air, add chapter titles, and export a clean training video" → Download MP4. Takes 1-3 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. ## Tips and Tricks The backend processes faster when you're specific. Instead of "make it look better", try "cut dead air, add chapter titles, and export a clean training video" — 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 LMS platforms like Teachable and Thinkific.


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