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peand-rover

Ai Image To Video Joyfun

by peandrover adam · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install ai-image-to-video-joyfun
Description
Get animated video clips ready to post, without touching a single slider. Upload your still images (JPG, PNG, WEBP, HEIC, up to 200MB), say something like "a...
README (SKILL.md)

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 creation.

Try saying:

  • "convert a single product photo or illustration into a 1080p MP4"
  • "animate this image into a smooth 5-second video clip"
  • "turning static images into short animated videos for social media creators"

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 Image to Video JoyFun — Convert Images into Video Clips

Drop your still 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 a single product photo or illustration, ask for animate this image into a smooth 5-second video clip, 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 — high-contrast images with clear subjects animate more smoothly.

Matching Input to Actions

User prompts referencing ai image to video joyfun, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is ai-image-to-video-joyfun, 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).

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/\x3Csid>/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_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> 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.

SSE Event Handling

Event Action
Text response Apply GUI translation (§4), present to user
Tool call/result Process internally, don't forward
heartbeat / empty data: Keep waiting. Every 2 min: "⏳ Still working..."
Stream closes Process 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.

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 JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

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 into a smooth 5-second video clip" — 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.

Common Workflows

Quick edit: Upload → "animate this image into a smooth 5-second video clip" → 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.

Usage Guidance
This skill appears to be a thin integration with the nemovideo.ai rendering service and needs a NEMO_TOKEN to operate. Things to consider before installing: - Confirm you trust the domain mega-api-prod.nemovideo.ai and the skill author (source unknown, no homepage). - If you don't want the skill to obtain credentials for you, set NEMO_TOKEN yourself (do not paste private tokens into chat). Otherwise the skill will call the anonymous-token endpoint and persist the returned token for 7 days. - The skill asks the agent to detect install paths (~/.clawhub, ~/.cursor/skills) and references ~/.config/nemovideo/ — decide whether you are comfortable with the agent reading those filesystem locations. - Only upload images you are willing to send to an external service; uploads and exports will go to the service's API endpoints. - If you need higher assurance, request the skill source or a trusted homepage, or ask the author to remove filesystem-detection behavior. Revoke any auto-generated tokens you don't recognize. Why I marked this suspicious: minor inconsistencies (declared configPaths in SKILL.md vs registry metadata) and the instruction to probe local install/config paths expand the agent's read scope beyond the minimal needs for uploading images. More provenance (source/homepage) or removal of unnecessary filesystem access would raise confidence.
Capability Analysis
Type: OpenClaw Skill Name: ai-image-to-video-joyfun Version: 1.0.0 The skill facilitates image-to-video conversion by interfacing with the nemovideo.ai API. It includes standard procedures for authentication (using NEMO_TOKEN or anonymous UUIDs), file uploads, and polling for render status. The instructions are consistent with the stated purpose, and while it performs basic environment detection for telemetry (checking for Cursor or ClawHub installation paths), there is no evidence of malicious data exfiltration or unauthorized system access.
Capability Assessment
Purpose & Capability
The declared primaryEnv (NEMO_TOKEN) and the API endpoints in SKILL.md align with an image-to-video cloud service. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) and references detecting install paths for header population, which is inconsistent with the registry metadata that said no required config paths and is not strictly necessary for the stated purpose.
Instruction Scope
Runtime instructions direct the agent to obtain or generate a bearer token, create sessions, upload local files, and poll SSE endpoints on mega-api-prod.nemovideo.ai — all expected. But the instructions also tell the agent to detect an install path (~/.clawhub/ or ~/.cursor/skills/) and derive X-Skill-Platform from it, and reference a local config dir (~/.config/nemovideo/). This implies filesystem reads beyond just user-supplied images and may persist tokens/session IDs; that scope creep is not fully justified in the description.
Install Mechanism
Instruction-only skill with no install spec and no code files — lowest install risk. All runtime behavior is network/API oriented.
Credentials
Only one credential is required: NEMO_TOKEN (declared as primaryEnv). That is appropriate for a cloud rendering service. The skill also describes generating an anonymous token via an API call if no env var is provided — acceptable but means the skill will autonomously obtain and store credentials if run without a pre-set token.
Persistence & Privilege
Skill is not always-enabled and does not request elevated platform privileges. It does instruct saving session_id and token values for operation, which is normal for service sessions but means credentials may be persisted to agent state or local config if implemented.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install ai-image-to-video-joyfun
  3. After installation, invoke the skill by name or use /ai-image-to-video-joyfun
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of AI Image to Video JoyFun. - Instantly animate still images (JPG, PNG, WEBP, HEIC, up to 200MB) to 1080p MP4 videos for social media. - Fully automated cloud workflow with one-step upload, AI video generation, and quick download. - No animation or editing experience needed — just describe your desired result. - Supports key video editing actions: export, balance checking, timeline preview, and more.
Metadata
Slug ai-image-to-video-joyfun
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Ai Image To Video Joyfun?

Get animated video clips ready to post, without touching a single slider. Upload your still images (JPG, PNG, WEBP, HEIC, up to 200MB), say something like "a... It is an AI Agent Skill for Claude Code / OpenClaw, with 66 downloads so far.

How do I install Ai Image To Video Joyfun?

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

Is Ai Image To Video Joyfun free?

Yes, Ai Image To Video Joyfun is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Ai Image To Video Joyfun support?

Ai Image To Video Joyfun is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Ai Image To Video Joyfun?

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

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