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francemichaell-15

Image To Video Imagemover

作者 francemichaell-15 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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当前安装
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版本数
在 OpenClaw 中安装
/install image-to-video-imagemover
功能描述
convert still images into animated video clips with this skill. Works with JPG, PNG, WEBP, HEIC files up to 200MB. social media creators use it for convertin...
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 five product photos in JPG format into a 1080p MP4"
  • "turn my images into a smooth video with transitions and music"
  • "converting photo collections into shareable 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.

Image to Video ImageMover — 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 five product photos in JPG format, type "turn my images into a smooth video with transitions and music", and you'll get a 1080p MP4 back in roughly 30-90 seconds. All rendering happens server-side.

Worth noting: using images with consistent aspect ratios produces cleaner transitions.

Matching Input to Actions

User prompts referencing image to video imagemover, 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.

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

  • X-Skill-Source: image-to-video-imagemover
  • 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.

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.

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

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 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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn my images into a smooth video with transitions and music" — 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 platforms.

Common Workflows

Quick edit: Upload → "turn my images into a smooth video with transitions and music" → 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.

安全使用建议
This skill appears to implement a cloud-based image→video workflow and only needs a NEMO_TOKEN to operate, which is reasonable. Before installing: 1) Confirm the NEMO API domain (https://mega-api-prod.nemovideo.ai) is trustworthy and that you accept their privacy/retention policy — images you upload will be sent to that service. 2) Ask the skill author to explain the discrepancy between registry metadata and the SKILL.md frontmatter (the latter mentions ~/.config/nemovideo/). Clarify whether the skill will read that directory or other local files. 3) The skill instructs detecting install paths (~/.clawhub, ~/.cursor/skills); if you don't want the agent to probe your home directory, decline or sandbox the skill. 4) Use an ephemeral or limited-scope token if possible, test with non-sensitive images first, and rotate/revoke the token after use if you have any doubts.
功能分析
Type: OpenClaw Skill Name: image-to-video-imagemover Version: 1.0.0 The skill bundle is a legitimate integration for the NemoVideo image-to-video cloud service. It provides instructions for an AI agent to manage API authentication, session handling, file uploads, and video rendering via the 'mega-api-prod.nemovideo.ai' endpoint. While it includes logic for the agent to fingerprint its installation environment (e.g., checking for ~/.cursor/skills/ or ~/.clawhub/) for attribution headers, there is no evidence of data exfiltration, unauthorized command execution, or malicious intent.
能力评估
Purpose & Capability
The name/description, declared primary credential (NEMO_TOKEN), and all API endpoints in SKILL.md align with an image→video cloud-rendering service. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) and instructions to detect install paths (~/.clawhub, ~/.cursor/skills) while the registry metadata lists no required config paths — this mismatch should be clarified by the author.
Instruction Scope
Runtime instructions are detailed and largely within scope: create/obtain a NEMO_TOKEN, create a session, upload image files (multipart or by URL), stream SSEs, poll render status, and return a download URL. A notable instruction asks the agent to detect an install path on the host (checking ~/, ~/.clawhub, ~/.cursor/skills) to set an attribution header; that requires reading the local filesystem (home directory). Reading these specific locations is not obviously necessary for video rendering and expands the skill's runtime scope.
Install Mechanism
Instruction-only (no install spec, no code files). This minimizes install-time risk because nothing is written to disk by an installer step.
Credentials
Only a single credential (NEMO_TOKEN) is required, which is proportional to a remote API service. However, the frontmatter declares a config path (~/.config/nemovideo/) which was not listed in the registry metadata — if the skill reads that directory it might access local tokens/configs, so confirm whether that path is actually needed.
Persistence & Privilege
always is false and the skill does not request persistent platform-level privileges. It does instruct the agent to save session_id and use tokens for API calls (normal for a cloud render workflow) but does not request to modify other skills or system-wide settings.
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-imagemover
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /image-to-video-imagemover 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 ImageMover - Convert still images (JPG, PNG, WEBP, HEIC up to 200MB) into 1080p MP4 video clips in 30–90 seconds. - Automatic session, token, and API setup with free trial support (100 credits, 7-day expiry). - Upload image files, generate videos with transitions, background music, and text overlays—ideal for social media creators. - Full cloud rendering pipeline with download links and session persistence for editing workflows. - Handles errors (token/session, file size/type, credits, usage limits) with clear user messages and actionable suggestions.
元数据
Slug image-to-video-imagemover
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 Imagemover 是什么?

convert still images into animated video clips with this skill. Works with JPG, PNG, WEBP, HEIC files up to 200MB. social media creators use it for convertin... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 65 次。

如何安装 Image To Video Imagemover?

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

Image To Video Imagemover 是免费的吗?

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

Image To Video Imagemover 支持哪些平台?

Image To Video Imagemover 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 Imagemover?

由 francemichaell-15(@francemichaell-15)开发并维护,当前版本 v1.0.0。

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