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dsewell-583h0

Image To Video Ai Joy

作者 dsewell-583h0 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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当前安装
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在 OpenClaw 中安装
/install image-to-video-ai-joy
功能描述
Get animated video clips ready to post, without touching a single slider. Upload your still images (JPG, PNG, WEBP, HEIC, up to 200MB), say something like "t...
使用说明 (SKILL.md)

Getting Started

Got still images to work with? Send it over and tell me what you need — I'll take care of the AI video creation.

Try saying:

  • "convert three vacation photos in JPG format into a 1080p MP4"
  • "turn my photos into a smooth animated video with transitions"
  • "turning still photos into dynamic AI-generated videos for social media creators"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

  1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
  2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer \x3Ctoken>, Content-Type: application/json, and body {"task_name":"project","language":"\x3Cdetected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Image to Video AI Joy — Turn Photos into Animated Videos

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 three vacation photos in JPG format and want to turn my photos into a smooth animated video with transitions — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: images with clear subjects and simple backgrounds produce smoother motion results.

Matching Input to Actions

User prompts referencing image to video ai joy, 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.

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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

  • X-Skill-Source: image-to-video-ai-joy
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else 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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn my photos into a smooth animated video with 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 my photos into a smooth animated video with 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 appears to do what it says: it uploads images to a cloud service (mega-api-prod.nemovideo.ai) and returns rendered video results. Before installing or using it: (1) be aware your images will be sent off-host to that API — do not upload sensitive/private images unless you trust the service and have reviewed its privacy terms; (2) the skill may store an anonymous session token and session_id locally for subsequent requests — consider how long that data should persist in your environment; (3) note small metadata inconsistencies (declared required env var vs. anonymous-token flow, and a configPath in frontmatter) — these are likely benign but you may want the publisher to clarify whether the skill will read ~/.config/nemovideo/ or always create/require its own token; (4) if you need stronger isolation, prefer running uploads via an account token you control (set NEMO_TOKEN yourself) rather than relying on anonymously minted tokens.
功能分析
Type: OpenClaw Skill Name: image-to-video-ai-joy Version: 1.0.0 The skill provides a functional interface for an image-to-video AI service hosted at nemovideo.ai. It includes logic for automated anonymous authentication, session management, and polling for video rendering tasks. While it performs environment fingerprinting to determine the host platform (e.g., checking for ~/.clawhub or ~/.cursor paths), this is used for API attribution headers and aligns with the stated purpose of the tool. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found in SKILL.md or _meta.json.
能力评估
Purpose & Capability
Name/description (image → video) matches the APIs and the single declared credential (NEMO_TOKEN). Minor inconsistency: the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata reported no required config paths. Also the registry lists NEMO_TOKEN as required, but SKILL.md contains a flow to obtain an anonymous token automatically if none is present.
Instruction Scope
Instructions are focused on authenticating, creating a session, uploading images, invoking SSE/messages, checking credits/state, and exporting renders. They do not instruct the agent to read arbitrary user files, system secrets, or unrelated environment variables. The only filesystem/environment reads implied are: (a) reading this skill's frontmatter for attribution and (b) detecting install path to set X-Skill-Platform; both are limited in scope but worth noting.
Install Mechanism
Instruction-only skill with no install spec or downloadable code, so nothing new is written to disk beyond normal session storage by the agent. This is the lowest install risk.
Credentials
The single primary credential requested is NEMO_TOKEN, which is appropriate for a cloud render service. However, SKILL.md can auto-request an anonymous NEMO_TOKEN if none exists, so the 'required env var' declaration is inconsistent with the runtime flow. The frontmatter's configPaths entry (~/.config/nemovideo/) could imply reading a local config, but the runtime instructions do not require it.
Persistence & Privilege
The skill is not always-enabled and does not request elevated or cross-skill privileges. It does instruct the agent to store session_id and token for subsequent calls (normal for API sessions), but it does not instruct modifying other skills or global agent config.
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-ai-joy
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /image-to-video-ai-joy 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 Joy. - Instantly turns uploaded photos (JPG, PNG, WEBP, HEIC) into 1080p MP4 videos with AI-powered animation and smooth transitions. - Fast setup: automatic authentication and session creation for new users; supports 100 free credits per token. - Supports social media-friendly exports, batch processing, and real-time project editing with timeline summaries. - Automated error handling and concise feedback for common edge cases (credits, file size, supported formats, etc.). - Streamlined user prompts with no need for manual configuration or complex animation software.
元数据
Slug image-to-video-ai-joy
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 Ai Joy 是什么?

Get animated video clips ready to post, without touching a single slider. Upload your still images (JPG, PNG, WEBP, HEIC, up to 200MB), say something like "t... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 66 次。

如何安装 Image To Video Ai Joy?

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

Image To Video Ai Joy 是免费的吗?

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

Image To Video Ai Joy 支持哪些平台?

Image To Video Ai Joy 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 Ai Joy?

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

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