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tk8544-b

Image To Video Ai Unrestricted

作者 tk8544-b · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install image-to-video-ai-unrestricted
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 "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 single product photo or portrait image into a 1080p MP4"
  • "animate this image into a 5-second video clip with motion"
  • "converting static images into moving video content without content restrictions for content creators, marketers, artists"

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 Unrestricted — Convert Images Into Video Clips

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 single product photo or portrait image and want to animate this image into a 5-second video clip with motion — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: high-contrast images with clear subjects produce smoother and more realistic motion output.

Matching Input to Actions

User prompts referencing image to video ai unrestricted, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is image-to-video-ai-unrestricted, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise 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 field mapping: t=tracks, tt=track type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

Common Workflows

Quick edit: Upload → "animate this image into a 5-second video clip with motion" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "animate this image into a 5-second video clip with motion" — 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 video editors.

安全使用建议
This skill will upload whatever images and prompts the user provides to https://mega-api-prod.nemovideo.ai and may create an anonymous NEMO_TOKEN on your behalf if you don't supply one. Before installing or using it: (1) do not upload sensitive or private images unless you trust the service; (2) understand that the 'unrestricted' claim may allow generation of content that violates platform policies or laws — check your legal/organizational rules; (3) the skill's metadata says you must provide NEMO_TOKEN but the runtime will obtain an anonymous token automatically, so if you want control supply your own token or avoid installation; (4) verify the service origin and privacy policy if possible; (5) consider testing with non-sensitive images and monitoring network activity or logs. If you want me to, I can extract every API path/ header the SKILL.md will call and produce a minimal checklist for network allowlisting or review.
功能分析
Type: OpenClaw Skill Name: image-to-video-ai-unrestricted Version: 1.0.0 The skill is a functional integration for the 'nemovideo.ai' image-to-video service. It provides the OpenClaw agent with instructions for authentication (including automated anonymous token generation), session management, and API interaction for uploading images and rendering videos. While it explicitly markets itself as 'unrestricted' to bypass content filters, the code and instructions are strictly limited to the service's API (mega-api-prod.nemovideo.ai) and do not show evidence of data exfiltration, unauthorized local file access, or malicious command execution.
能力评估
Purpose & Capability
Name and description claim an image→video cloud service and the instructions call the mega-api-prod.nemovideo.ai backend — this is coherently aligned. The declared required env (NEMO_TOKEN) and config path (~/.config/nemovideo/) are plausible for such a service, but the SKILL.md also describes creating an anonymous token automatically if NEMO_TOKEN is missing, so the declared requirement is inconsistent with the runtime instructions.
Instruction Scope
Runtime instructions instruct the agent to upload user-provided image files and to POST/ poll multiple endpoints on mega-api-prod.nemovideo.ai (session creation, SSE, file upload, render/export). That is expected for a cloud render service, but it means user files and prompts will be sent to an external API. The skill also advertises being 'unrestricted' (bypassing content filters), which increases legal/privacy/abuse risk even though it is not a technical incoherence by itself.
Install Mechanism
No install spec or code files — instruction-only skill; nothing is written to disk by an installer (lowest install risk).
Credentials
The registry marks NEMO_TOKEN as required (primaryEnv), but SKILL.md explicitly documents creating an anonymous token via the anonymous-token endpoint when NEMO_TOKEN is absent. This is an inconsistency: the skill can operate without the user-supplied credential. Also a config path (~/.config/nemovideo/) is declared in metadata but the instructions don't require reading that path. Otherwise the skill requests only one credential, which is proportionate for a cloud API.
Persistence & Privilege
always:false and normal autonomous invocation are used. The skill uses transient session tokens and renders API calls; it does not request permanent system-wide privileges or modify other skills. Token lifetime is short (7 days) per the instructions and the skill reconnects as needed.
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-unrestricted
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /image-to-video-ai-unrestricted 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 Unrestricted (v1.0.0) - Instantly animates your still images (JPG, PNG, WEBP, HEIC, up to 200MB) into 1080p MP4 video clips via cloud AI processing - No platform content restrictions or filters; designed for content creators, marketers, and artists - Automatic setup with anonymous cloud session and token generation (100 free credits, 7-day expiry) - Supports batch uploads, iterative editing, and quick exports across multiple media formats - Streamlined commands for upload, animation, export, credits, and session state
元数据
Slug image-to-video-ai-unrestricted
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 Unrestricted 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 "a... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 63 次。

如何安装 Image To Video Ai Unrestricted?

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

Image To Video Ai Unrestricted 是免费的吗?

是的,Image To Video Ai Unrestricted 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 Unrestricted 支持哪些平台?

Image To Video Ai Unrestricted 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 Unrestricted?

由 tk8544-b(@tk8544-b)开发并维护,当前版本 v1.0.0。

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