Skill: peand-rover/image-to-video-loop-ai (version 1.0.0)

--- name: image-to-video-loop-ai version: "1.0.0" displayName: "Image to Video Loop AI — Convert Images Into Looping Videos" description: > Get looping video clips ready to post, without touching a single slider. Upload your still images (JPG, PNG, WEBP, HEIC, up to 200MB), say something like "turn this image into a seamlessly looping video clip", and download 1080p MP4 when it's done. Built for social media creators who move fast and want to animate static images into looping videos without manual editing. metadata: {"openclaw": {"emoji": "🔁", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "short_prompts"}} --- ## Getting Started > Share your still images and I'll get started on AI loop video creation. Or just tell me what you're thinking. **Try saying:** - "convert my still images" - "export 1080p MP4" - "turn this image into a seamlessly" ### 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. # Image to Video Loop AI — Convert Images Into Looping Videos This tool takes your still images and runs AI loop video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result. Say you have a single product photo or landscape image and want to turn this image into a seamlessly looping video clip — the backend processes it in about 20-40 seconds and hands you a 1080p MP4. Tip: high-contrast images with clear subjects produce the smoothest loops. ## Matching Input to Actions User prompts referencing image to video loop 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. 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. Headers are derived from this file's YAML frontmatter. `X-Skill-Source` is `image-to-video-loop-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`). Include `Authorization: Bearer <NEMO_TOKEN>` and all attribution headers on every request — omitting them triggers a 402 on export. ### 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 | ### 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. ### 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 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 "turn this image into a seamlessly looping video clip" — concrete instructions get better results. Max file size is 200MB. Stick to JPG, PNG, WEBP, HEIC for the smoothest experience. Export as MP4 for widest compatibility across Instagram, TikTok, and YouTube. ## Common Workflows **Quick edit**: Upload → "turn this image into a seamlessly looping video clip" → Download MP4. Takes 20-40 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.


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