Skill: peand-rover/text-to-video-kiss (version 1.0.0)

--- name: text-to-video-kiss version: "1.0.0" displayName: "Text to Video Kiss — Generate Kiss Scenes from Text" description: > Get AI-generated video clips ready to post, without touching a single slider. Upload your text prompt (TXT, DOCX, PDF, plain text, up to 500MB), say something like "generate a romantic kiss scene from a written description", and download 1080p MP4 when it's done. Built for filmmakers, storytellers, content creators who move fast and want to visualize romantic scenes without filming actors. metadata: {"openclaw": {"emoji": "💋", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "short_prompts"}} --- ## Getting Started > Share your text prompt and I'll get started on AI video generation. Or just tell me what you're thinking. **Try saying:** - "generate my text prompt" - "export 1080p MP4" - "generate a romantic kiss scene from" ### 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. # Text to Video Kiss — Generate Kiss Scenes from Text Send me your text prompt and describe the result you want. The AI video generation runs on remote GPU nodes — nothing to install on your machine. A quick example: upload a short description like 'two people sharing a kiss at sunset on a beach', type "generate a romantic kiss scene from a written description", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side. Worth noting: shorter, more specific prompts produce more accurate and consistent results. ## Matching Input to Actions User prompts referencing text to video kiss, 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 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. Headers are derived from this file's YAML frontmatter. `X-Skill-Source` is `text-to-video-kiss`, `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`). **API base**: `https://mega-api-prod.nemovideo.ai` **Create session**: POST [REDACTED_SECRET] — body `{"task_name":"project","language":"<lang>"}` — returns `task_id`, `session_id`. **Send message (SSE)**: POST `/run_sse` — body `{"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}}` with `Accept: text/event-stream`. Max timeout: 15 minutes. **Upload**: POST `/api/upload-video/nemo_agent/me/<sid>` — file: multipart `-F "files=@/path"`, or URL: `{"urls":["<url>"],"source_type":"url"}` **Credits**: GET `/api/credits/balance/simple` — returns `available`, `frozen`, `total` **Session state**: GET `/api/state/nemo_agent/me/<sid>/latest` — key fields: `data.state.draft`, `data.state.video_infos`, `data.state.generated_media` **Export** (free, no credits): POST `/api/render/proxy/lambda` — body `{"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}`. Poll GET `/api/render/proxy/lambda/<id>` every 30s until `status` = `completed`. Download URL at `output.url`. Supported formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac. ### 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 ### 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. 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) ``` ## Tips and Tricks The backend processes faster when you're specific. Instead of "make it look better", try "generate a romantic kiss scene from a written description" — concrete instructions get better results. Max file size is 500MB. Stick to TXT, DOCX, PDF, plain text for the smoothest experience. Export as MP4 for widest compatibility across social and editing platforms. ## Common Workflows **Quick edit**: Upload → "generate a romantic kiss scene from a written description" → Download MP4. Takes 1-2 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.


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