/install ai-image-to-video-kissing
Getting Started
Send me your still images and I'll handle the AI video generation. Or just describe what you're after.
Try saying:
- "convert a single portrait photo of two people close together into a 1080p MP4"
- "animate this image into a short kissing scene video clip"
- "animating romantic portrait photos into short video moments for couples, content creators, social media users"
Automatic Setup
On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".
Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.
Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: \x3Cuuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).
Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.
Confirm to the user you're connected and ready. Don't print tokens or raw JSON.
AI Image to Video Kissing — Animate Photos into Video Clips
This tool takes your still images and runs AI video generation through a cloud rendering pipeline. You upload, describe what you want, and download the result.
Say you have a single portrait photo of two people close together and want to animate this image into a short kissing scene video clip — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.
Tip: high-resolution face photos with clear lighting produce the most realistic animation results.
Matching Input to Actions
User prompts referencing ai image to video kissing, 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 |
|---|---|---|
/api/tasks/me/with-session/nemo_agent |
POST | Start a new editing session. Body: {"task_name":"project","language":"\x3Clang>"}. 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/\x3Csid> |
POST | Upload a file (multipart) or URL. |
/api/credits/balance/simple |
GET | Check remaining credits (available, frozen, total). |
/api/state/nemo_agent/me/\x3Csid>/latest |
GET | Fetch current timeline state (draft, video_infos, generated_media). |
/api/render/proxy/lambda |
POST | Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"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.
Three attribution headers are required on every request and must match this file's frontmatter:
| Header | Value |
|---|---|
X-Skill-Source |
ai-image-to-video-kissing |
X-Skill-Version |
frontmatter version |
X-Skill-Platform |
auto-detect: clawhub / cursor / unknown from install path |
All requests must include: Authorization: Bearer \x3CNEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.
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=\x3Cid> (get \x3Cid> 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 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)
Tips and Tricks
The backend processes faster when you're specific. Instead of "make it look better", try "animate this image into a short kissing scene 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 social platforms.
Common Workflows
Quick edit: Upload → "animate this image into a short kissing scene video clip" → Download MP4. Takes 30-60 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.
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install ai-image-to-video-kissing - After installation, invoke the skill by name or use
/ai-image-to-video-kissing - Provide required inputs per the skill's parameter spec and get structured output
What is Ai Image To Video Kissing?
Skip the learning curve of professional editing software. Describe what you want — animate this image into a short kissing scene video clip — and get animate... It is an AI Agent Skill for Claude Code / OpenClaw, with 65 downloads so far.
How do I install Ai Image To Video Kissing?
Run "/install ai-image-to-video-kissing" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Ai Image To Video Kissing free?
Yes, Ai Image To Video Kissing is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Ai Image To Video Kissing support?
Ai Image To Video Kissing is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Ai Image To Video Kissing?
It is built and maintained by mory128 (@mory128); the current version is v1.0.0.