Skill: susan4731-wilfordf/neural-frames-ai (version 1.0.0)

--- name: neural-frames-ai version: "1.0.0" displayName: "Neural Frames AI — Generate Videos from Text Prompts" description: > Turn a written prompt describing a cinematic landscape scene into 1080p AI generated videos just by typing what you need. Whether it's generating short AI animated videos from text prompts or quick social content, drop your text prompts and describe the result you want. No timeline dragging, no export settings — 1-3 minutes from upload to download. metadata: {"openclaw": {"emoji": "🎞️", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "greeting_v2"}} --- ## Getting Started > Got text prompts to work with? Send it over and tell me what you need — I'll take care of the AI video generation. **Try saying:** - "generate a written prompt describing a cinematic landscape scene into a 1080p MP4" - "generate a 10-second animated video from the prompt 'neon city at night with rain'" - "generating short AI animated videos from text prompts for digital artists, content creators, AI enthusiasts" ### 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. # Neural Frames AI — 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 written prompt describing a cinematic landscape scene and want to generate a 10-second animated video from the prompt 'neon city at night with rain' — the backend processes it in about 1-3 minutes and hands you a 1080p MP4. Tip: shorter prompts with clear visual descriptions produce more consistent results. ## Matching Input to Actions User prompts referencing neural frames ai, 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. Include `Authorization: Bearer <NEMO_TOKEN>` and all attribution headers on every request — omitting them triggers a 402 on export. Headers are derived from this file's YAML frontmatter. `X-Skill-Source` is `neural-frames-ai`, `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 ### 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 | ### 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) ``` ## Common Workflows **Quick edit**: Upload → "generate a 10-second animated video from the prompt 'neon city at night with rain'" → 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 animated video from the prompt 'neon city at night with rain'" — concrete instructions get better results. Max file size is 500MB. Stick to MP4, PNG, JPG, GIF for the smoothest experience. Export as MP4 for widest compatibility across social platforms.


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