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tk8544-b

Image To Video Explicit Ai

by tk8544-b · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install image-to-video-explicit-ai
Description
Turn a single character illustration or photo into 1080p animated video clips just by typing what you need. Whether it's converting adult images into animate...
README (SKILL.md)

Getting Started

Share your static images and I'll get started on AI video generation. Or just tell me what you're thinking.

Try saying:

  • "convert my static images"
  • "export 1080p MP4"
  • "animate this image into a short"

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 Explicit AI — Animate Images into Video Clips

This tool takes your static images and runs AI video generation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a single character illustration or photo and want to animate this image into a short explicit adult video clip with motion — the backend processes it in about 1-3 minutes and hands you a 1080p MP4.

Tip: higher resolution input images produce sharper and more detailed output video.

Matching Input to Actions

User prompts referencing image to video explicit 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.

All requests must include: Authorization: Bearer \x3CNEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is image-to-video-explicit-ai, 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

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

  • "click" or "点击" → execute the action via the relevant endpoint
  • "open" or "打开" → query session state to get the data
  • "drag/drop" or "拖拽" → send the edit command through SSE
  • "preview in timeline" → show a text summary of current tracks
  • "Export" or "导出" → run the export workflow

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.

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)

Common Workflows

Quick edit: Upload → "animate this image into a short explicit adult video clip with motion" → Download MP4. Takes 1-3 minutes 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 short explicit adult video clip with motion" — concrete instructions get better results.

Max file size is 200MB. Stick to JPG, PNG, WEBP, BMP for the smoothest experience.

Use PNG input for best quality output since it preserves detail without compression artifacts.

Usage Guidance
This skill will upload any images you give it (including explicit adult images) to an external service at mega-api-prod.nemovideo.ai and will create or use a NEMO_TOKEN credential for that service. There is no installable client to inspect and the skill's origin/homepage are unknown. Before installing: (1) only use it with images you are comfortable uploading to a third party; (2) do not upload images of minors or anything you are not legally allowed to share; (3) be aware the skill may fingerprint your environment (it derives a platform header from install paths) and will create anonymous tokens if none are provided; (4) prefer skills with a known source or an inspectable client; (5) if you must proceed, verify the remote domain and its privacy/terms, and avoid setting persistent credentials unless you trust the service.
Capability Analysis
Type: OpenClaw Skill Name: image-to-video-explicit-ai Version: 1.0.0 The skill bundle provides a functional interface for an AI video generation service (nemovideo.ai). It includes detailed instructions for the agent to manage API tokens, sessions, and file uploads. While the skill focuses on 'explicit adult content,' which may be a policy concern for some platforms, the technical implementation lacks indicators of security malice such as unauthorized data exfiltration, shell execution, or persistence. The filesystem access mentioned in SKILL.md is limited to reading its own configuration and identifying its installation path for telemetry headers (X-Skill-Platform).
Capability Assessment
Purpose & Capability
The name/description (image → video, including explicit adult content) aligns with the instructions to upload images and call a cloud rendering API that returns MP4s. However the SKILL.md metadata requests a configuration path (~/.config/nemovideo/) while the registry metadata lists no required config paths — an inconsistency in declared surface area. The skill's source/homepage are unknown, which increases the risk of relying on an external service without provenance.
Instruction Scope
The runtime instructions tell the agent to: check NEMO_TOKEN, and if missing generate a UUID and call an external anonymous-auth endpoint to create a token; create sessions, upload local files (multipart) or URLs, and poll render endpoints. These actions necessarily transmit user images (including explicit content) to an external domain. The instructions also direct the agent to derive an attribution header by probing the agent's install path (fingerprinting the environment). Those behaviors go beyond simple local processing and have clear privacy/exfiltration risk; they are coherent with the stated purpose but raise concerns about unintended data disclosure and environment fingerprinting.
Install Mechanism
No install spec and no code files are present (instruction-only). That reduces surface risk from arbitrary downloaded code, but it also means there is no inspectable client implementation; runtime behavior depends wholly on the agent following these instructions to contact the external API.
Credentials
The skill only needs a single credential (NEMO_TOKEN), which is appropriate for a cloud API. However the SKILL.md metadata includes a configPaths entry (~/.config/nemovideo/) that is not declared in the registry metadata — inconsistent. The skill also instructs the agent to produce an anonymous token if NEMO_TOKEN is absent, which is logical but means the skill will unilaterally create and store credentials and will upload user-provided files to a remote service. These actions are proportionate for the stated function but carry privacy and credential-handling implications that users should understand.
Persistence & Privilege
always: false and the skill does not request special system privileges. It instructs keeping a session_id for the session lifecycle (normal). No instructions to modify other skills or global agent configuration were found.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install image-to-video-explicit-ai
  3. After installation, invoke the skill by name or use /image-to-video-explicit-ai
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of "Image to Video Explicit AI" — instantly animate static images or character illustrations into 1080p video clips via cloud AI processing. - Simple upload and prompt system: users describe the animation needed and receive a rendered video in 1–3 minutes. - Automated cloud backend setup on first use; supports anonymous sessions with free credits (requires no manual token management). - One-click export to MP4 and common formats, with timeline-based action mapping for edits, credits, and status. - Built-in error handling and progress updates, including session management and helpful prompts for common issues. - Supports quick edits, batch processing, and iterative workflows, optimized for adult and explicit content transformation.
Metadata
Slug image-to-video-explicit-ai
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Image To Video Explicit Ai?

Turn a single character illustration or photo into 1080p animated video clips just by typing what you need. Whether it's converting adult images into animate... It is an AI Agent Skill for Claude Code / OpenClaw, with 74 downloads so far.

How do I install Image To Video Explicit Ai?

Run "/install image-to-video-explicit-ai" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Image To Video Explicit Ai free?

Yes, Image To Video Explicit Ai is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Image To Video Explicit Ai support?

Image To Video Explicit Ai is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Image To Video Explicit Ai?

It is built and maintained by tk8544-b (@tk8544-b); the current version is v1.0.0.

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