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Image To Video Online Converter

v1.0.0

Get animated MP4 video ready to post, without touching a single slider. Upload your images (JPG, PNG, WEBP, GIF, up to 200MB), say something like "turn these...

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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 francemichaell-15/image-to-video-online-converter.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Image To Video Online Converter" (francemichaell-15/image-to-video-online-converter) from ClawHub.
Skill page: https://clawhub.ai/francemichaell-15/image-to-video-online-converter
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-online-converter

ClawHub CLI

Package manager switcher

npx clawhub@latest install image-to-video-online-converter
Security Scan
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OpenClawOpenClaw
Suspicious
medium confidence
Purpose & Capability
The stated purpose (upload images, render MP4 via a cloud backend) aligns with the endpoints and workflows described. Requesting a NEMO_TOKEN is coherent for a cloud service. However, the SKILL.md metadata lists a config path (~/.config/nemovideo/) that is not reflected in the registry's 'required config paths' summary — this mismatch is unexplained and worth clarifying.
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Instruction Scope
Runtime instructions direct the agent to: check for NEMO_TOKEN, call the service's anonymous-token endpoint if absent, POST uploads and create sessions, and poll render status — all expected. But the skill also instructs the agent to read this file's YAML frontmatter and detect the agent's install path to populate X-Skill-Version and X-Skill-Platform, and references a user config directory (~/.config/nemovideo/). Those steps require reading local files/paths beyond simple network calls and are not fully declared in the registry metadata, increasing the surface for unintended local information access.
Install Mechanism
There is no install spec or downloadable code; the skill is instruction-only. That reduces disk/write risk because nothing additional is installed by the skill itself.
Credentials
The skill only requires a single credential (NEMO_TOKEN), which is proportionate for a cloud rendering API. It also describes fetching an anonymous token from the service when none is present (network call). The metadata's mention of a config path is inconsistent with the registry and suggests potential access to local configuration; that should be justified before granting access to any sensitive tokens.
Persistence & Privilege
The skill is not always-enabled and does not request elevated platform privileges or to modify other skills. Autonomous invocation remains enabled (normal), but there is no indication the skill persists or changes system-wide settings.
Scan Findings in Context
[no_regex_findings] expected: The static regex scanner found no code to analyze (instruction-only SKILL.md). Absence of findings is expected for an instruction-only skill but does not imply safety.
What to consider before installing
This skill mostly does what it claims (it uploads images to a cloud render API and returns MP4s), but exercise caution: 1) The package has no homepage or known source — verify the domain (mega-api-prod.nemovideo.ai) and vendor before sending sensitive images or credentials. 2) It requires or will mint a NEMO_TOKEN; if you don't have one, it will call the anonymous-token endpoint (network call) and treat the returned token as a credential — avoid supplying any other reusable or high-privilege tokens. 3) Ask the publisher why the SKILL.md metadata references ~/.config/nemovideo/ and why the agent needs to read install paths/frontmatter; if you are uncomfortable with local file reads, do not install. 4) If you try it, test with non-sensitive sample images and a disposable token/anonymous flow first, and review the service's privacy/terms for data retention and access to uploaded media.

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

Runtime requirements

🖼️ Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97bzzsq4mgahpepteycywsdps84xjrq
59downloads
0stars
1versions
Updated 1w 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 photos into a 30-second"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

  • Generate a UUID as client identifier
  • POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
  • Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Image to Video Online Converter — Convert Photos into MP4 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 photos into a 30-second video with transitions and background music — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: using images with consistent dimensions gives smoother transitions in the final video.

Matching Input to Actions

User prompts referencing image to video online converter, 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 calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> every 30s for completed status and download URL.

Formats: 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: image-to-video-online-converter
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

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.

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)

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

SSE Event Handling

EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultProcess internally, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess 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.

Error Codes

  • 0 — success, continue normally
  • 1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token
  • 1002 — session not found; create a new one
  • 2001 — out of credits; anonymous users get a registration link with ?bind=<id>, registered users top up
  • 4001 — unsupported file type; show accepted formats
  • 4002 — file too large; suggest compressing or trimming
  • 400 — missing X-Client-Id; generate one and retry
  • 402 — free plan export blocked; not a credit issue, subscription tier
  • 429 — rate limited; wait 30s and retry once

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn these photos into a 30-second 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 across social platforms and devices.

Common Workflows

Quick edit: Upload → "turn these photos into a 30-second 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.

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