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dsewell-583h0

Image To Video Hunyuan

by dsewell-583h0 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install image-to-video-hunyuan
Description
Turn a single product photo or landscape image into 1080p animated video clips just by typing what you need. Whether it's turning static images into short an...
README (SKILL.md)

Getting Started

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

Try saying:

  • "convert my still images"
  • "export 1080p MP4"
  • "animate this image into a 5-second"

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.

Image to Video Hunyuan — Animate Images into Video Clips

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

Say you have a single product photo or landscape image and want to animate this image into a 5-second video clip using HunyuanVideo — the backend processes it in about 1-3 minutes and hands you a 1080p MP4.

Tip: images with clear subjects and simple backgrounds produce smoother motion results.

Matching Input to Actions

User prompts referencing image to video hunyuan, 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.

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source: image-to-video-hunyuan
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else 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 Handling

Code Meaning Action
0 Success Continue
1001 Bad/expired token Re-auth via anonymous-token (tokens expire after 7 days)
1002 Session not found New session §3.0
2001 No credits Anonymous: show registration URL with ?bind=\x3Cid> (get \x3Cid> from create-session or state response when needed). Registered: "Top up credits in your account"
4001 Unsupported file Show supported formats
4002 File too large Suggest compress/trim
400 Missing X-Client-Id Generate Client-Id and retry (see §1)
402 Free plan export blocked Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429 Rate limit (1 token/client/7 days) Retry in 30s once

Common Workflows

Quick edit: Upload → "animate this image into a 5-second video clip using HunyuanVideo" → Download MP4. Takes 1-3 minutes 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "animate this image into a 5-second video clip using HunyuanVideo" — concrete instructions get better results.

Max file size is 20MB. Stick to JPG, PNG, WEBP, BMP for the smoothest experience.

Use PNG for input images to preserve quality and avoid compression artifacts.

Usage Guidance
This skill appears to do what it says: call nemovideo.ai to turn images into short videos and requires a NEMO_TOKEN. Before installing: 1) Confirm whether the skill will read ~/.config/nemovideo/ (the SKILL.md frontmatter mentions it, but the registry metadata did not). 2) Only provide a NEMO_TOKEN you trust (use a limited-scope or short-lived token if possible); the skill can also obtain a 7-day anonymous token automatically. 3) Be aware the agent will send your images to mega-api-prod.nemovideo.ai — don’t upload sensitive images unless you trust their handling and retention policy. 4) If you’re uncomfortable with the skill inspecting install paths to set attribution headers, ask the skill author to remove or document that behavior. If these points are acceptable, the skill’s requested access looks proportionate to its function.
Capability Analysis
Type: OpenClaw Skill Name: image-to-video-hunyuan Version: 1.0.0 The skill bundle provides instructions for an AI agent to interface with the HunyuanVideo API via `mega-api-prod.nemovideo.ai`. It includes logic for automated anonymous authentication, session management, and handling media uploads/exports. While it asks the agent to identify its installation environment (e.g., checking for `~/.clawhub/` or `~/.cursor/skills/`) for attribution headers, this behavior is transparently documented and aligned with the tool's stated purpose. No evidence of data exfiltration, malicious command execution, or unauthorized access to sensitive system credentials was found.
Capability Assessment
Purpose & Capability
The skill is an image→video generator and declares only a NEMO_TOKEN credential which is appropriate for calling a cloud render API. The API endpoints and operations in SKILL.md match the described purpose. Note: SKILL.md metadata references a config path (~/.config/nemovideo/) even though the registry metadata listed no config paths — this mismatch should be confirmed.
Instruction Scope
Runtime instructions stay focused on session creation, SSE chat, file upload, and export workflows against https://mega-api-prod.nemovideo.ai. It also documents an anonymous-token flow if NEMO_TOKEN is missing. One operational detail to note: the skill asks the agent to determine an X-Skill-Platform header by detecting install paths (e.g., checking ~/.clawhub/ or ~/.cursor/skills/), which implies inspecting the filesystem to decide a header value — this is reasonable for attribution but is out-of-band from pure image processing and worth verifying.
Install Mechanism
Instruction-only skill with no install spec or code to download — lowest-risk delivery method. Nothing is written to disk by an installer according to the provided metadata.
Credentials
The single required env var (NEMO_TOKEN) is proportionate to a cloud API integration. The SKILL.md also references a config path (~/.config/nemovideo/) in its frontmatter, which could indicate it expects to read local config or cached tokens; confirm whether the agent will access that directory and what it would read there before granting access.
Persistence & Privilege
always is false and there is no install-time persistent presence requested. The skill will create short-lived session tokens and expects the agent to hold session_id/state in memory; autonomous invocation is allowed by default but not excessive here.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install image-to-video-hunyuan
  3. After installation, invoke the skill by name or use /image-to-video-hunyuan
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of Image to Video Hunyuan skill. - Turn a single product photo or landscape image into 1080p animated video clips in 1-3 minutes. - Simple workflow: upload an image, describe the animation you want, and download the result. - Supports key actions via chat prompts: export, upload, check credits, or manage timeline state. - Built-in cloud rendering pipeline—no local export required. - Free trial with 100 credits; supports common video and image formats (mp4, mov, avi, jpg, png, etc).
Metadata
Slug image-to-video-hunyuan
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Image To Video Hunyuan?

Turn a single product photo or landscape image into 1080p animated video clips just by typing what you need. Whether it's turning static images into short an... It is an AI Agent Skill for Claude Code / OpenClaw, with 87 downloads so far.

How do I install Image To Video Hunyuan?

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

Is Image To Video Hunyuan free?

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

Which platforms does Image To Video Hunyuan support?

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

Who created Image To Video Hunyuan?

It is built and maintained by dsewell-583h0 (@dsewell-583h0); the current version is v1.0.0.

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