Skill: francemichaell-15/text-to-video-models (version 1.0.0)

--- name: text-to-video-models version: "1.0.0" displayName: "Text to Video Models — Generate Videos from Text Prompts" description: > Skip the learning curve of professional editing software. Describe what you want — generate a 10-second clip of a sunset over a city skyline with cinematic camera movement — and get AI generated clips back in 1-3 minutes. Upload TXT, DOCX, PDF, CSV files up to 500MB, and the AI handles AI video generation automatically. Ideal for marketers, content creators, filmmakers who want to create video content without cameras or editing software. metadata: {"openclaw": {"emoji": "🎬", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "greeting_v2"}} --- ## Getting Started > Send me your text prompts and I'll handle the AI video generation. Or just describe what you're after. **Try saying:** - "generate a two-sentence scene description into a 1080p MP4" - "generate a 10-second clip of a sunset over a city skyline with cinematic camera movement" - "generating video clips from written scene descriptions for marketers, content creators, filmmakers" ### 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. # Text to Video Models — Generate Videos from Text Prompts This tool takes your text prompts and runs AI video generation through a cloud rendering pipeline. You upload, describe what you want, and download the result. Say you have a two-sentence scene description and want to generate a 10-second clip of a sunset over a city skyline with cinematic camera movement — the backend processes it in about 1-3 minutes and hands you a 1080p MP4. Tip: shorter and more specific prompts tend to produce more accurate and consistent results. ## Matching Input to Actions User prompts referencing text to video models, 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` | `text-to-video-models` | | `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) ``` ### Backend Response Translation The backend assumes a GUI exists. Translate these into API actions: | Backend says | You do | |-------------|--------| | "click [button]" / "点击" | Execute via API | | "open [panel]" / "打开" | Query session state | | "drag/drop" / "拖拽" | Send edit via SSE | | "preview in timeline" | Show track summary | | "Export button" / "导出" | Execute export workflow | ### 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. ### 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 → "generate a 10-second clip of a sunset over a city skyline with cinematic camera movement" → 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 "generate a 10-second clip of a sunset over a city skyline with cinematic camera movement" — concrete instructions get better results. Max file size is 500MB. Stick to TXT, DOCX, PDF, CSV for the smoothest experience. Export as MP4 for widest compatibility across social and web platforms.


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