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Image To Video Examples

作者 linmillsd7 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install image-to-video-examples
功能描述
Skip the learning curve of professional editing software. Describe what you want — turn these product photos into a 10-second video with smooth transitions —...
使用说明 (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"
  • "turn these product photos into a"

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 Examples — Convert Photos Into Video Clips

Drop your still 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 in JPG format, ask for turn these product photos into a 10-second video with smooth transitions, 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 examples, 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-examples
  • 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 product photos into a 10-second video with smooth transitions" — 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.

Common Workflows

Quick edit: Upload → "turn these product photos into a 10-second video with smooth transitions" → 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 is coherent for a cloud image→video service, but it will upload any images you provide to an external domain (mega-api-prod.nemovideo.ai) and may create an anonymous token automatically if you don't supply NEMO_TOKEN. Before installing/using it: (1) avoid uploading sensitive images unless you trust the service; (2) if you want control over billing/retention, supply your own NEMO_TOKEN from a trusted account; (3) check ~/.config/nemovideo/ after use for any cached tokens or session files; (4) review nemovideo.ai's privacy/terms if possible; and (5) be aware the agent will make outbound network requests and poll SSE endpoints to render and return files.
功能分析
Type: OpenClaw Skill Name: image-to-video-examples Version: 1.0.0 The skill bundle provides instructions and API documentation for an AI agent to interface with the 'nemovideo.ai' service for image-to-video conversion. It includes standard procedures for anonymous authentication, session management, and handling asynchronous video rendering via SSE and polling. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found; the instructions are strictly aligned with the stated purpose of the skill.
能力评估
Purpose & Capability
Name/description match the actions in SKILL.md: connecting to a nemovideo.ai backend, uploading images, creating render jobs, polling SSE and returning video URLs. The declared primary env var (NEMO_TOKEN) and config path (~/.config/nemovideo/) are consistent with a cloud backend client.
Instruction Scope
Instructions remain focused on the image→video workflow (session creation, uploads, SSE, render/export). They also instruct the agent to generate an anonymous token if NEMO_TOKEN is missing and to read the install path to set an attribution header — these are within the service workflow but do cause the agent to probe local paths and automatically contact an external API when no token is provided.
Install Mechanism
No install spec or code files — instruction-only skill (lowest disk-write risk). All network activity is performed at runtime via described API endpoints rather than by installing binaries.
Credentials
Only one declared credential (NEMO_TOKEN) and a single config path are requested, which fits the service. The skill will auto-obtain an anonymous NEMO_TOKEN if none is present, which is convenient but means the agent will automatically call an external auth endpoint and use that token for subsequent uploads and renders.
Persistence & Privilege
always:false and normal model invocation. The skill keeps a session_id for operations (ephemeral session behavior described); it does not request always-on presence or modify other skills. Autonomous network calls and file uploads are expected for this kind of cloud service.
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-examples
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /image-to-video-examples 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 Examples — Convert Photos Into Video Clips. - Instantly converts uploaded still images (JPG, PNG, WEBP, HEIC, up to 200MB) into 1080p MP4 video clips with smooth transitions using a cloud backend. - Automatic session and token setup for easy onboarding; 100 free credits included for first-time users. - Quick workflows for exporting, editing, previewing, and customizing videos—ideal for marketers and content creators. - Supports intent-based actions such as export, check credits, upload, and edit, all routed by user prompt. - Handles multiple input formats and responsive to error scenarios (credits, file type, size, rate limits) with clear feedback.
元数据
Slug image-to-video-examples
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 Examples 是什么?

Skip the learning curve of professional editing software. Describe what you want — turn these product photos into a 10-second video with smooth transitions —... 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 Image To Video Examples?

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

Image To Video Examples 是免费的吗?

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

Image To Video Examples 支持哪些平台?

Image To Video Examples 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 Examples?

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

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