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Ai Animation Generator From Image

by peandrover adam · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install ai-animation-generator-from-image
Description
convert still images into animated video clips with this skill. Works with JPG, PNG, WEBP, HEIC files up to 200MB. social media creators use it for turning s...
README (SKILL.md)

Getting Started

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

Try saying:

  • "convert my still images"
  • "export 1080p MP4"
  • "animate this image with a slow"

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 Animation Generator from Image — Convert Images into Animated Videos

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

Here's a typical use: you send a a single product photo or portrait, ask for animate this image with a slow zoom and natural motion, and about 20-40 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — high-contrast images with clear subjects animate more smoothly.

Matching Input to Actions

User prompts referencing ai animation generator from image, 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.

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":"\x3Clang>"}. 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/\x3Csid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/\x3Csid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s for completed status and download URL.

Formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is ai-animation-generator-from-image, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).

Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 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 says You 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

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.

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=\x3Cid>, 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 "animate this image with a slow zoom and natural motion" — 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.

Common Workflows

Quick edit: Upload → "animate this image with a slow zoom and natural motion" → Download MP4. Takes 20-40 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.

Usage Guidance
This skill appears to be what it says (cloud-based image→video rendering) but check a few things before you install/use it: 1) Confirm you trust the host domain (mega-api-prod.nemovideo.ai) — images and generated tokens are uploaded there. 2) The skill will use NEMO_TOKEN if present or request an anonymous token (which becomes a bearer credential). Consider using a disposable token or account if you are unsure. 3) Ask the author to clarify the mismatch: the registry metadata lists no config paths but SKILL.md frontmatter references ~/.config/nemovideo/ — find out whether tokens or session IDs will be written to that directory. 4) Be aware the skill may check common install paths (~/.clawhub/, ~/.cursor/skills/) to set an attribution header; if you do not want that filesystem probing, request a version without that behavior. 5) Confirm privacy/retention and billing (credits, free token expiry) before uploading sensitive or private images.
Capability Analysis
Type: OpenClaw Skill Name: ai-animation-generator-from-image Version: 1.0.0 The skill is a legitimate integration for an AI video generation service (nemovideo.ai). It defines standard REST and SSE API interactions for uploading images, managing sessions, and polling for rendered video files. The instructions in SKILL.md are well-structured, include error handling, and specifically advise the agent against leaking authentication tokens in the chat interface, which is a security best practice.
Capability Assessment
Purpose & Capability
The skill claims to convert still images to animated videos and all runtime instructions describe calling a remote rendering API that requires a NEMO_TOKEN and session management — this is coherent with the stated purpose. The declared primaryEnv (NEMO_TOKEN) fits the functionality.
Instruction Scope
SKILL.md instructs the agent to: use an existing NEMO_TOKEN or obtain an anonymous token by POSTing to https://mega-api-prod.nemovideo.ai, create and save a session_id, upload files, read SSE streams, poll job status, and translate backend GUI prompts to API calls. Those actions are expected for a cloud-rendering service. Two things to note: (1) the skill asks the agent to detect install path (e.g. ~/.clawhub/, ~/.cursor/skills/) to set an attribution header — that requires checking the filesystem and could reveal environment layout; (2) the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) but the top-level registry metadata said no config paths — this mismatch is inconsistent and worth asking the author to clarify.
Install Mechanism
There is no install spec and no code files — this is an instruction-only skill. That is the lowest-risk pattern from an installation perspective (nothing is downloaded or executed locally by the skill).
Credentials
Only NEMO_TOKEN is declared as required, which is proportionate for a service that needs a bearer token. However, the skill also describes generating an anonymous token (which becomes a bearer token) and instructs saving session state (and frontmatter references a config path). Confirm whether the skill will persist tokens/session data to ~/.config/nemovideo/ and whether the runtime will read that directory — the registry metadata and SKILL.md disagree about configPaths.
Persistence & Privilege
The skill is not always-enabled and does not request elevated platform-wide privileges. It does instruct saving a session_id and may persist tokens/session info (normal for a service client). The filesystem checks for install path (to set X-Skill-Platform) are an additional, modest privacy consideration but not a high privilege escalation.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install ai-animation-generator-from-image
  3. After installation, invoke the skill by name or use /ai-animation-generator-from-image
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
AI Animation Generator from Image — v1.0.0 - Initial release of the skill to convert still images (JPG, PNG, WEBP, HEIC up to 200MB) into animated 1080p MP4 video clips. - Automatic setup connects to the processing API and manages tokens and session creation for users. - Supports basic workflows: uploading images, requesting animations, adding simple edits, and exporting videos. - Provides prompts for common tasks (convert, animate, export) and a robust error-handling guide. - Includes cloud render pipeline and detailed user feedback for uploads, processing, and export status. - Designed for social media content creators to easily animate images with minimal setup.
Metadata
Slug ai-animation-generator-from-image
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Ai Animation Generator From Image?

convert still images into animated video clips with this skill. Works with JPG, PNG, WEBP, HEIC files up to 200MB. social media creators use it for turning s... It is an AI Agent Skill for Claude Code / OpenClaw, with 96 downloads so far.

How do I install Ai Animation Generator From Image?

Run "/install ai-animation-generator-from-image" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Ai Animation Generator From Image free?

Yes, Ai Animation Generator From Image is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Ai Animation Generator From Image support?

Ai Animation Generator From Image is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Ai Animation Generator From Image?

It is built and maintained by peandrover adam (@peand-rover); the current version is v1.0.0.

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