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A2e Image To Video

作者 susan4731-wilfordf · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install a2e-image-to-video
功能描述
Skip the learning curve of professional editing software. Describe what you want — turn this image into a 10-second animated video with smooth motion — and g...
使用说明 (SKILL.md)

Getting Started

Ready when you are. Drop your still images here or describe what you want to make.

Try saying:

  • "convert a single product photo or landscape image into a 1080p MP4"
  • "turn this image into a 10-second animated video with smooth motion"
  • "converting static images into short animated videos for marketers, social media creators"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

  • Generate a UUID as client identifier
  • POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
  • The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

A2E Image to Video — 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 landscape image, type "turn this image into a 10-second animated video 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 produce the most natural-looking motion.

Matching Input to Actions

User prompts referencing a2e image to video, 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 requests must include: Authorization: Bearer \x3CNEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is a2e-image-to-video, 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).

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 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

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

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 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)

Common Workflows

Quick edit: Upload → "turn this image into a 10-second animated video 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn this image into a 10-second animated video with smooth motion" — concrete instructions get better results.

Max file size is 50MB. Stick to JPG, PNG, WEBP, HEIC for the smoothest experience.

Export as MP4 for widest compatibility across social platforms.

安全使用建议
This skill appears to do what it says: send images to a remote NemoVideo API to produce short videos. Before installing / using it, consider: (1) NEMO_TOKEN (or the anonymous token the skill can fetch) grants the remote service access to any images you upload — avoid uploading sensitive personal data unless you trust nemo video and understand their retention/privacy policy; (2) the SKILL.md references a config path (~/.config/nemovideo/) that the registry metadata did not declare — confirm whether the integration will read that directory or any local files beyond the images you explicitly upload; (3) the skill will make outbound HTTPS calls to https://mega-api-prod.nemovideo.ai — confirm you are comfortable sending media and prompts to that domain; (4) prefer supplying your own NEMO_TOKEN if you want tighter control over access/credentials. These are precautionary checks; there are no strong technical red flags suggesting the skill is doing unrelated or malicious work.
功能分析
Type: OpenClaw Skill Name: a2e-image-to-video Version: 1.0.0 The skill is a functional integration for an AI image-to-video service hosted at nemovideo.ai. It provides instructions for an AI agent to manage sessions, upload images, and trigger video rendering via a remote API. While the skill performs network requests and file uploads, these actions are essential for its stated purpose of converting images to video. The instructions include specific error handling and telemetry headers (X-Skill-Platform) but show no evidence of malicious intent, data exfiltration, or unauthorized system access.
能力评估
Purpose & Capability
Name/description match the instructions: the SKILL.md describes calling a remote NemoVideo API to create/ render short videos from uploaded images. Requesting a single service token (NEMO_TOKEN) is appropriate for this purpose.
Instruction Scope
Instructions are focused on the NemoVideo API (session creation, SSE for generation, upload, export/polling). They explicitly require uploading user files (multipart or URL) and may read local file paths for uploads. The doc also tells the agent to detect install path (~/.clawhub, ~/.cursor/skills/) to set an X-Skill-Platform header — this implies inspecting those paths which is plausible but broader than strictly necessary. No unrelated system-wide secrets or arbitrary file reads are requested in the instructions.
Install Mechanism
Instruction-only skill with no install spec and no code files. Nothing is downloaded or written by an installer. This is the lowest-risk install model.
Credentials
The declared primary environment variable is a single service token (NEMO_TOKEN), which is appropriate. However the SKILL.md frontmatter also references a config path (~/.config/nemovideo/) not declared in the registry metadata — a small inconsistency. The skill also supports generating an anonymous token if no NEMO_TOKEN is present, which is expected behavior but means the service can be used without a user-supplied credential.
Persistence & Privilege
always is false and there is no install-time persistence. The skill does not request or assert permanent presence or system-wide configuration changes.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install a2e-image-to-video
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /a2e-image-to-video 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of a2e-image-to-video skill. - Instantly convert still images (JPG, PNG, WEBP, HEIC up to 50MB) into animated video clips via a simple chat prompt. - Automated backend session and token management for hassle-free connections. - Cloud GPU-powered rendering; no local installs or advanced editing required. - Supports video customization: aspect ratios, text overlays, audio tracks, and more. - Includes easy workflows for quick edits, batch processing, and timeline refinement.
元数据
Slug a2e-image-to-video
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

A2e Image To Video 是什么?

Skip the learning curve of professional editing software. Describe what you want — turn this image into a 10-second animated video with smooth motion — and g... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 70 次。

如何安装 A2e Image To Video?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install a2e-image-to-video」即可一键安装,无需额外配置。

A2e Image To Video 是免费的吗?

是的,A2e Image To Video 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

A2e Image To Video 支持哪些平台?

A2e Image To Video 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 A2e Image To Video?

由 susan4731-wilfordf(@susan4731-wilfordf)开发并维护,当前版本 v1.0.0。

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