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linmillsd7

Image To Video Midjourney

作者 linmillsd7 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install image-to-video-midjourney
功能描述
Get animated video clips ready to post, without touching a single slider. Upload your still images (PNG, JPG, WEBP, JPEG, up to 200MB), say something like "a...
使用说明 (SKILL.md)

Getting Started

Send me your still images and I'll handle the AI video creation. Or just describe what you're after.

Try saying:

  • "convert a Midjourney-generated portrait or landscape image into a 1080p MP4"
  • "animate this Midjourney image into a smooth 5-second video clip"
  • "turning Midjourney images into short animated video clips for AI artists and content 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.

Image to Video Midjourney — Animate Midjourney Images to Video

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

Say you have a Midjourney-generated portrait or landscape image and want to animate this Midjourney image into a smooth 5-second video clip — the backend processes it in about 30-90 seconds and hands you a 1080p MP4.

Tip: high-contrast images with clear subjects animate more smoothly than busy or abstract compositions.

Matching Input to Actions

User prompts referencing image to video midjourney, 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-midjourney
  • 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 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)

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

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

Common Workflows

Quick edit: Upload → "animate this Midjourney image into a smooth 5-second video clip" → Download MP4. Takes 30-90 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 "animate this Midjourney image into a smooth 5-second video clip" — concrete instructions get better results.

Max file size is 200MB. Stick to PNG, JPG, WEBP, JPEG for the smoothest experience.

Export your Midjourney image as PNG before uploading to preserve the highest quality detail.

安全使用建议
This skill appears to do what it says (upload images to a Nemo render API and return videos), but there are a few things to check before installing: 1) Source and trust: there is no homepage or known publisher—prefer skills from a verifiable source. 2) Token scope: only provide a NEMO_TOKEN that is limited in scope/permissions and not reused for other services; if unsure, let the skill obtain an anonymous starter token rather than sharing a long-lived secret. 3) Filesystem probing: the skill may inspect install paths (~/.clawhub/, ~/.cursor/skills/) and mentions ~/.config/nemovideo/ in its metadata — ask the publisher why that config path is needed and insist it not read other user files. 4) Network endpoints: all traffic goes to mega-api-prod.nemovideo.ai — confirm this domain is legitimate for the service. If you need higher assurance, ask for the skill's source code or a homepage and for the registry metadata to be corrected (the registry reported no config paths while the skill frontmatter declares one). Providing those details would raise confidence and could change this assessment to benign.
功能分析
Type: OpenClaw Skill Name: image-to-video-midjourney Version: 1.0.0 The skill provides a functional integration for converting images to videos using the nemovideo.ai API. It includes detailed instructions for session management, authentication via tokens, and handling media uploads and exports. While it directs the agent to check local installation paths (e.g., ~/.cursor/skills/) for platform attribution headers, these actions are transparently documented and aligned with the skill's stated purpose of providing a streamlined AI video creation workflow.
能力评估
Purpose & Capability
Name/description align with using a cloud render API to convert still images to short videos. Requiring NEMO_TOKEN is appropriate for an API-backed service. However, the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) and runtime behavior to detect the agent install path for attribution headers — these are not clearly necessary for the core animation function and mismatch the registry summary (which listed no config paths).
Instruction Scope
Instructions focus on the Nemo API flows (auth, session creation, upload, SSE, export) and on sending user images to the cloud — this is consistent. The skill also instructs the agent to: read this file's YAML frontmatter, detect the agent's install path (e.g., ~/.clawhub/, ~/.cursor/skills/) to set an X-Skill-Platform header, and potentially access ~/.config/nemovideo/. Reading its own frontmatter is benign; probing install paths and an extra config directory is additional filesystem access beyond the minimum needed to upload an image and call the API.
Install Mechanism
No install spec or code files — instruction-only. This is lower-risk because nothing is downloaded or written to disk by the skill itself.
Credentials
Only NEMO_TOKEN is declared and used as the primary credential, which is proportionate. But the frontmatter's configPaths entry (~/.config/nemovideo/) and the implied filesystem probing are unexpected and not explained. The skill also offers to obtain an anonymous token by POSTing to an external endpoint if NEMO_TOKEN is absent — network token acquisition is reasonable, but users should be aware the skill will contact an external service and receive a bearer token to use on their behalf.
Persistence & Privilege
always:false and no install hooks are present. The skill does not request persistent system-wide privileges or to modify other skills. Autonomous invocation is enabled (default) but not combined with other high-risk flags.
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 image-to-video-midjourney
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /image-to-video-midjourney 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 “Image to Video Midjourney — Animate Midjourney Images to Video”. Users can easily animate still Midjourney images into short, ready-to-post video clips. - Upload a PNG, JPG, WEBP, or JPEG (up to 200MB), give simple instructions, and receive a 1080p MP4 video. - No manual editing; just describe what you want (e.g., “animate this Midjourney image into a smooth 5-second video clip”). - Automatic session and token handling, with 100 free credits for new users. - Fast cloud rendering: get downloadable animated video in about 30–90 seconds. - Includes workflows for uploading, editing, previewing, exporting, and managing credits — all chat-driven. - Smart error handling and clear user status messages.
元数据
Slug image-to-video-midjourney
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

Image To Video Midjourney 是什么?

Get animated video clips ready to post, without touching a single slider. Upload your still images (PNG, JPG, WEBP, JPEG, up to 200MB), say something like "a... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 91 次。

如何安装 Image To Video Midjourney?

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

Image To Video Midjourney 是免费的吗?

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

Image To Video Midjourney 支持哪些平台?

Image To Video Midjourney 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 Image To Video Midjourney?

由 linmillsd7(@linmillsd7)开发并维护,当前版本 v1.0.0。

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