Image To Video Ai Free Online

v1.0.0

convert static images into animated video clips with this image-to-video-ai-free-online skill. Works with JPG, PNG, WEBP, GIF files up to 200MB. social media...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for dsewell-583h0/image-to-video-ai-free-online.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Image To Video Ai Free Online" (dsewell-583h0/image-to-video-ai-free-online) from ClawHub.
Skill page: https://clawhub.ai/dsewell-583h0/image-to-video-ai-free-online
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: NEMO_TOKEN
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install image-to-video-ai-free-online

ClawHub CLI

Package manager switcher

npx clawhub@latest install image-to-video-ai-free-online
Security Scan
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OpenClawOpenClaw
Benign
medium confidence
Purpose & Capability
The name/description claim image→video conversion and the SKILL.md only describes creating a session, uploading images, and requesting renders from a nemo-video backend (mega-api-prod.nemovideo.ai). Requesting NEMO_TOKEN as the primary credential is coherent with that purpose.
Instruction Scope
Runtime instructions are scoped to API calls (auth, session creation, SSE, upload, render/poll). They direct the agent to use NEMO_TOKEN if present or obtain an anonymous token, and to upload files or URLs. One minor scope detail: the skill says to auto-detect X-Skill-Platform from an install path, which implies reading an install path/environment to determine platform — this is implementation-specific but not excessive for header attribution.
Install Mechanism
No install spec and no code files — instruction-only. Nothing is downloaded or written to disk by an installer, which lowers installation risk.
Credentials
Only NEMO_TOKEN is declared as required, which fits the service. However, SKILL.md frontmatter's metadata includes a configPaths entry (~/.config/nemovideo/) that was not reflected in the registry summary; if the agent reads that path it could access local configuration or tokens. This discrepancy should be clarified.
Persistence & Privilege
always:false and no special persistence or system-wide changes are requested. Autonomous invocation is allowed (default) but that is expected for skills; the skill does not request elevated privileges or to modify other skills.
Assessment
This skill appears to do what it says: it talks to a nemo-video API, uses a NEMO_TOKEN (or gets an anonymous token), uploads images, and returns render URLs. Before installing, confirm you trust the backend domain (mega-api-prod.nemovideo.ai) and where your images will be sent. Note the SKILL.md metadata mentions ~/.config/nemovideo/ (config path) even though the registry summary listed no config paths — ask the author whether the skill will read that directory. If you supply a long-lived NEMO_TOKEN, treat it as a credential for that service; consider using an anonymous token for sensitive images or verifying the service privacy terms. The lack of a homepage/author information is another reason to be cautious; if you need higher assurance, request a link to official docs or a vetted source before enabling the skill.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🖼️ Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk9733d09d4py9ewdenmk42yv3184jfs3
92downloads
0stars
1versions
Updated 2w ago
v1.0.0
MIT-0

Getting Started

Send me your static images and I'll handle the AI video creation. Or just describe what you're after.

Try saying:

  • "convert three product photos in JPG format into a 1080p MP4"
  • "turn these photos into a smooth video with transitions"
  • "converting still photos into shareable video content for social media creators"

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.

Image to Video AI Free Online — Convert Images into Video Clips

Drop your static images in the chat and tell me what you need. I'll handle the AI video creation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a three product photos in JPG format, ask for turn these photos into a smooth video with transitions, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — using fewer images with higher resolution gives smoother output.

Matching Input to Actions

User prompts referencing image to video ai free online, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip 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.

Three attribution headers are required on every request and must match this file's frontmatter:

HeaderValue
X-Skill-Sourceimage-to-video-ai-free-online
X-Skill-Versionfrontmatter version
X-Skill-Platformauto-detect: clawhub / cursor / unknown from install path

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — 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 Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s 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

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.

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 "turn these photos into a smooth video with transitions" — concrete instructions get better results.

Max file size is 200MB. Stick to JPG, PNG, WEBP, GIF for the smoothest experience.

Export as MP4 for widest compatibility.

Common Workflows

Quick edit: Upload → "turn these photos into a smooth video with transitions" → 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.

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