Ai Image To Video Effects
/install ai-image-to-video-effects
Getting Started
Got still images to work with? Send it over and tell me what you need — I'll take care of the AI video effects generation.
Try saying:
- "convert a single product photo or landscape image into a 1080p MP4"
- "animate this image with a cinematic zoom and motion blur effect"
- "turning static images into animated video clips with motion effects for social media creators, marketers, photographers"
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-tokenwith theX-Client-Idheader - The response includes a
tokenwith 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.
AI Image to Video Effects — Animate Images Into Video Clips
Send me your still images and describe the result you want. The AI video effects generation runs on remote GPU nodes — nothing to install on your machine.
A quick example: upload a single product photo or landscape image, type "animate this image with a cinematic zoom and motion blur effect", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.
Worth noting: high-contrast images with clear subjects produce the most noticeable motion effects.
Matching Input to Actions
User prompts referencing ai image to video effects, 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.
Skill attribution — read from this file's YAML frontmatter at runtime:
X-Skill-Source:ai-image-to-video-effectsX-Skill-Version: from frontmatterversionX-Skill-Platform: detect from install path (~/.clawhub/→clawhub,~/.cursor/skills/→cursor, elseunknown)
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 |
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.
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 with a cinematic zoom and motion blur effect" — 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 and devices.
Common Workflows
Quick edit: Upload → "animate this image with a cinematic zoom and motion blur effect" → 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.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install ai-image-to-video-effects - 安装完成后,直接呼叫该 Skill 的名称或使用
/ai-image-to-video-effects触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Ai Image To Video Effects 是什么?
Skip the learning curve of professional editing software. Describe what you want — animate this image with a cinematic zoom and motion blur effect — and get... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 86 次。
如何安装 Ai Image To Video Effects?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install ai-image-to-video-effects」即可一键安装,无需额外配置。
Ai Image To Video Effects 是免费的吗?
是的,Ai Image To Video Effects 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Ai Image To Video Effects 支持哪些平台?
Ai Image To Video Effects 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Ai Image To Video Effects?
由 peandrover adam(@peand-rover)开发并维护,当前版本 v1.0.0。