← Back to Skills Marketplace
mory128

Ai Image To Video A2e

by mory128 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
72
Downloads
0
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install ai-image-to-video-a2e
Description
Skip the learning curve of professional editing software. Describe what you want — animate this image into a 5-second video clip with smooth motion — and get...
README (SKILL.md)

Getting Started

Share your still images and I'll get started on AI video creation. 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.

AI Image to Video A2E — Convert Images into Video Clips

Send me your still images and describe the result you want. The AI video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a single product photo or illustrated scene, type "animate this image into a 5-second video clip with smooth motion", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: high-contrast images with clear subjects animate more cleanly than busy backgrounds.

Matching Input to Actions

User prompts referencing ai image to video a2e, 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.

Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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

  • X-Skill-Source: ai-image-to-video-a2e
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

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.

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

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

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.

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)

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 with smooth 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 across social platforms and devices.

Common Workflows

Quick edit: Upload → "animate this image into a 5-second video clip with smooth motion" → 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 coherent: it sends user images to a remote nemovideo API and needs a NEMO_TOKEN or an anonymous token. Before installing or using it: 1) Note there is no homepage or published vendor info — consider this unverified software. 2) Don’t provide sensitive or private images (uploads go to an external service). 3) Prefer generating an anonymous token for testing rather than supplying long-lived/shared credentials. 4) Ask the author/vendor for a privacy/retention policy and billing/credit details (how long files are retained, whether data is used for model training, and whether exports may be blocked by tier). 5) Verify the API hostname (mega-api-prod.nemovideo.ai) and TLS certs if you can, and test with non-sensitive samples first. If the owner or domain cannot be verified, treat the skill as untrusted for sensitive content.
Capability Analysis
Type: OpenClaw Skill Name: ai-image-to-video-a2e Version: 1.0.0 The skill is a legitimate integration for an AI image-to-video conversion service hosted at mega-api-prod.nemovideo.ai. It defines standard API workflows for authentication, session management, file uploads, and polling for render results. The instructions in SKILL.md are well-aligned with the stated purpose, including security-conscious directives such as not printing raw tokens or JSON to the user.
Capability Assessment
Purpose & Capability
The name/description match the runtime instructions: everything described is about sending images and commands to a remote 'nemovideo' API and receiving rendered videos. Requiring a NEMO_TOKEN (the service auth) is proportionate. Minor inconsistency: registry metadata earlier listed no required config paths, but the skill frontmatter metadata references a config path (~/.config/nemovideo/) — this is likely informational but should be clarified.
Instruction Scope
SKILL.md confines actions to establishing anonymous or token auth, creating a session, sending SSE messages, uploading files, polling renders, and returning download URLs. It does not instruct the agent to read unrelated local files or unrelated environment variables. It does instruct the agent to detect its install path (to set an X-Skill-Platform header) and to read this file's YAML frontmatter for attribution — both are reasonable and confined to the skill's operation.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, which is the lowest-risk install model. There are no downloads or package installs described.
Credentials
Only one credential is requested: NEMO_TOKEN (declared as primaryEnv). The instructions also support generating a short-lived anonymous token when NEMO_TOKEN is absent. No unrelated secrets or additional environment variables are requested. This is proportionate to the stated purpose.
Persistence & Privilege
The skill is not marked always:true and does not request system-wide privileges. It asks to save session_id for job tracking (expected for session-based APIs). Autonomous invocation is allowed by default but is not combined with other red flags here.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install ai-image-to-video-a2e
  3. After installation, invoke the skill by name or use /ai-image-to-video-a2e
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
AI Image to Video A2E 1.0.0 — Initial Release - Instantly convert uploaded images (JPG, PNG, WEBP, HEIC) into animated video clips with a simple prompt, no editing skills needed. - Supports automatic cloud setup: handles API tokens, session management, and connections in the background. - Features keyword-driven workflow for uploading, exporting, credits checking, and video generation — all from chat. - Exports in multiple formats including MP4, with fast server-side GPU rendering (30–90 seconds per job). - Designed for marketers, content creators, and designers needing quick, high-quality image animation. - Guides users with concise, actionable feedback and clear error messages.
Metadata
Slug ai-image-to-video-a2e
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 A2e?

Skip the learning curve of professional editing software. Describe what you want — animate this image into a 5-second video clip with smooth motion — and get... It is an AI Agent Skill for Claude Code / OpenClaw, with 72 downloads so far.

How do I install Ai Image To Video A2e?

Run "/install ai-image-to-video-a2e" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Ai Image To Video A2e free?

Yes, Ai Image To Video A2e is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Ai Image To Video A2e support?

Ai Image To Video A2e is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Ai Image To Video A2e?

It is built and maintained by mory128 (@mory128); the current version is v1.0.0.

💬 Comments