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dsewell-583h0

Image To Video Create Ai

作者 dsewell-583h0 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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当前安装
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在 OpenClaw 中安装
/install image-to-video-create-ai
功能描述
Skip the learning curve of professional editing software. Describe what you want — turn these photos into a smooth video with transitions and background musi...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "convert three product photos or a single landscape image into a 1080p MP4"
  • "turn these photos into a smooth video with transitions and background music"
  • "turning still images into shareable video content for marketers, social media creators, small business owners"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

  • Generate a UUID as client identifier
  • POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
  • Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Image to Video AI Creator — Convert Images Into Video Clips

Drop your images in the chat and tell me what you need. I'll handle the AI video creation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a three product photos or a single landscape image, ask for turn these photos into a smooth video with transitions and background music, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — using high-resolution images produces noticeably smoother motion output.

Matching Input to Actions

User prompts referencing image to video create ai, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint Method Purpose
/api/tasks/me/with-session/nemo_agent POST Start a new editing session. Body: {"task_name":"project","language":"\x3Clang>"}. Returns session_id.
/run_sse POST Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/\x3Csid> POST Upload a file (multipart) or URL.
/api/credits/balance/simple GET Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/\x3Csid>/latest GET Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda POST Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: 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-create-ai
  • 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.

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

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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn these photos into a smooth video with transitions and background 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 social platforms and devices.

Common Workflows

Quick edit: Upload → "turn these photos into a smooth video with transitions and background music" → 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.

安全使用建议
This skill uploads your images and requests render jobs from an external service (mega-api-prod.nemovideo.ai). Before installing: 1) Confirm you trust that domain and the service's privacy policy — don't upload sensitive images unless you're comfortable they leave your device. 2) Note the manifest inconsistencies: the skill says NEMO_TOKEN is required but will also auto-create an anonymous token; decide whether you want the agent to request tokens on your behalf. 3) Ask the publisher for a homepage, privacy/terms links, and clarification on where anonymous tokens and any cached files are stored (the frontmatter references ~/.config/nemovideo/). 4) If you want tighter control, provide your own NEMO_TOKEN (only if you trust the service) or avoid installing the skill. Additional information that would raise confidence to benign: a known publisher/homepage, privacy policy, and consistent manifest fields (explicit config path and clear token-storage behavior).
功能分析
Type: OpenClaw Skill Name: image-to-video-create-ai Version: 1.0.0 The skill is a legitimate integration for an AI video generation service (nemovideo.ai). It provides detailed instructions for the agent to manage API sessions, handle file uploads, and process video rendering tasks. While it includes logic to detect its installation path (e.g., ~/.cursor/skills/) for platform attribution and generates a UUID for anonymous authentication, these behaviors are transparently documented and aligned with the tool's stated purpose of providing a cloud-based image-to-video service. No evidence of data exfiltration, malicious code execution, or harmful prompt injection was found.
能力评估
Purpose & Capability
The skill's name and description (convert images to video via cloud rendering) match the runtime instructions and endpoints. However, metadata and requirements are inconsistent: top-level metadata listed no config paths, but the skill frontmatter advertises ~/.config/nemovideo/; the registry requires NEMO_TOKEN yet the SKILL.md instructs the agent to automatically obtain an anonymous token if none is present. These mismatches reduce confidence in the manifest's accuracy.
Instruction Scope
Instructions are focused on uploading images and controlling render jobs via the nemovideo API, which is expected. They also instruct the agent to: read this SKILL.md frontmatter for attribution headers and detect its install path to populate a header (which implies reading local install path/metadata). While not clearly malicious, those file-system/agent-environment checks are beyond simple upload logic and should be noted. The skill will send user files and metadata to external endpoints (mega-api-prod.nemovideo.ai), which is necessary for cloud rendering but has privacy implications.
Install Mechanism
No install script or downloads are specified (instruction-only), so nothing is written to disk by the skill itself. This is the lowest-risk install mechanism.
Credentials
The skill declares a single primary credential (NEMO_TOKEN) which is appropriate for an external API. However, the SKILL.md instructs the agent to auto-request an anonymous token if NEMO_TOKEN is not present, which conflicts with the manifest claiming the env var is required. The frontmatter also references a config path (~/.config/nemovideo/) not present in the top-level registry metadata. These inconsistencies create ambiguity about what credentials or files the skill will read or create.
Persistence & Privilege
The skill is not always-enabled, does not include an install routine, and does not request system-wide configuration changes. It does require the agent to make outbound requests to the service, which is normal for a cloud-rendering skill.
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-create-ai
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /image-to-video-create-ai 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 AI Creator. - Instantly converts images (JPG, PNG, WEBP, HEIC) into 1080p MP4 videos with transitions and background music. - Simple, prompt-based workflow requires no video editing experience. - Seamless cloud setup: automatic token generation and session management. - Supports uploads up to 200MB and provides quick video exports (30–60 seconds). - Handles user requests for balance, status, video download, and workflow management with clear error handling.
元数据
Slug image-to-video-create-ai
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 Create Ai 是什么?

Skip the learning curve of professional editing software. Describe what you want — turn these photos into a smooth video with transitions and background musi... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 84 次。

如何安装 Image To Video Create Ai?

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

Image To Video Create Ai 是免费的吗?

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

Image To Video Create Ai 支持哪些平台?

Image To Video Create Ai 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 Create Ai?

由 dsewell-583h0(@dsewell-583h0)开发并维护,当前版本 v1.0.0。

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