Image Video Ai

v1.0.0

marketers convert images into animated video clips using this skill. Accepts JPG, PNG, WEBP, GIF up to 200MB, renders on cloud GPUs at 1080p, and returns MP4...

0· 97·0 current·0 all-time
bypeandrover adam@peand-rover

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for peand-rover/image-video-ai.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Image Video Ai" (peand-rover/image-video-ai) from ClawHub.
Skill page: https://clawhub.ai/peand-rover/image-video-ai
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-video-ai

ClawHub CLI

Package manager switcher

npx clawhub@latest install image-video-ai
Security Scan
VirusTotalVirusTotal
Benign
View report →
OpenClawOpenClaw
Benign
medium confidence
Purpose & Capability
The skill is described as a cloud video-rendering tool and its instructions exclusively call a nemo video API and require a NEMO_TOKEN; that credential and the described API endpoints align with the stated purpose.
Instruction Scope
Runtime instructions direct the agent to upload user images and interactive messages to https://mega-api-prod.nemovideo.ai, create or reuse an anonymous token, open sessions, read SSE, poll render status, and return download URLs — all expected for this service. This means user image data and metadata will be transmitted to an external cloud service (expected but privacy-relevant). The SKILL.md also requires adding attribution headers and auto-detecting an 'install path' for X-Skill-Platform, which may be ill-defined in some agent contexts.
Install Mechanism
There is no install spec or packaged code — instruction-only skill. This is lower-risk because nothing is downloaded or written by an installer.
Credentials
Only one credential is declared (NEMO_TOKEN), which matches the API usage. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata reported no required config paths — this inconsistency should be clarified. The anonymous-token flow (POST to the service to get a temporary token) is reasonable but means the agent will perform network auth on first use if no token is supplied.
Persistence & Privilege
The skill does not request always:true, does not modify other skills, and only instructs saving its own session_id. It can invoke autonomously (normal default) but it does not request elevated or persistent platform privileges.
Assessment
This skill appears to be what it says: a cloud-based image→video converter that uploads images to nemovideo.ai and returns MP4s. Before installing, consider: (1) Privacy — your images will be sent to an external service; avoid uploading sensitive images. (2) Credentials — provide either a temporary/anonymous token or a service token (NEMO_TOKEN); don't reuse sensitive long-lived keys. (3) Metadata inconsistency — the SKILL.md mentions a local config path (~/.config/nemovideo/) not shown in registry metadata; ask the publisher whether the agent will read or write that directory. (4) Source & trust — the skill has no homepage and an unknown source; verify the provider (mega-api-prod.nemovideo.ai) and its terms/privacy before use. If you need stronger assurance, ask the author to (a) publish a homepage/source repo, (b) remove or explicitly justify use of any local config paths, and (c) document privacy/retention policy for uploaded media.

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

Runtime requirements

🖼️ Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk970a3x1k312sqk9sdjcb7mx0h84jdj3
97downloads
0stars
1versions
Updated 2w ago
v1.0.0
MIT-0

Getting Started

Share your images and I'll get started on AI video creation. Or just tell me what you're thinking.

Try saying:

  • "convert my images"
  • "export 1080p MP4"
  • "turn these images into a slideshow"

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: <uuid>. 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.

Image Video AI — Convert Images Into Videos

This tool takes your images and runs AI video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have five product photos in JPG format and want to turn these images into a slideshow video with transitions and background music — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: using images of the same aspect ratio produces cleaner transitions.

Matching Input to Actions

User prompts referencing image video ai, 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.

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

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

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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.

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.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend saysYou 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

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)

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn these images into a slideshow video with transitions and background music" — 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 images into a slideshow video with transitions and background music" → 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.

Comments

Loading comments...