Ai Image To Video Create

Turn three product photos in JPG format into 1080p animated video clips just by typing what you need. Whether it's converting static images into shareable vi...

Security Scan

The skill's declared purpose (convert images to videos via a cloud API) is coherent with its runtime instructions, but there are a few mismatches and privacy-relevant behaviors you should understand before installing.

Purpose & Capability

The name/description (image-to-video conversion) matches the SKILL.md: it calls a remote rendering API, uploads images, and returns video downloads. Requiring a single service token (NEMO_TOKEN) is appropriate for this cloud service.

Instruction Scope

The instructions send user images and commands to a third-party API (https://mega-api-prod.nemovideo.ai), create sessions, stream SSE, and poll render jobs. This is expected for a cloud render service, but it means user files are transmitted off-device. The skill also instructs deriving some headers from the SKILL.md frontmatter and detecting an install path (to set X-Skill-Platform), which implies the agent may inspect its environment or paths—this is not necessary for core functionality and expands the scope of what the skill may read.

Install Mechanism

There is no install spec and no code files — the skill is instruction-only. That minimizes on-disk persistence and reduces supply-chain risk.

Credentials

The skill only requires NEMO_TOKEN (primaryEnv), which is proportionate to a cloud-rendering integration. However, the SKILL.md frontmatter also references a config path (~/.config/nemovideo/) and metadata-driven headers, but the registry metadata showed no required config paths — this mismatch is unexplained and could indicate the skill expects or will use local config files even though the registry didn't declare them.

Persistence & Privilege

The skill is not always-enabled and requests normal autonomous invocation ability. It creates ephemeral sessions and tokens via the API; it does not declare persistent system-wide privileges or modifications to other skills. Autonomous invocation combined with external uploads is normal here but increases blast radius if the skill were malicious.

What to consider before installing

This skill will upload whatever images you provide to mega-api-prod.nemovideo.ai and uses (or mints) a NEMO_TOKEN to authenticate. Before installing: (1) confirm you trust the nemo / nemovideo service and its privacy policy — do not upload sensitive images unless you accept third‑party processing; (2) prefer supplying your own NEMO_TOKEN if you need auditability (anonymous tokens expire and are minted automatically by the skill); (3) ask the publisher why the SKILL.md references a local config path (~/.config/nemovideo/) and install-path detection (this may cause the agent to inspect filesystem paths); (4) be aware the skill will send data to an external endpoint and can stream SSE responses and status; and (5) if you need higher assurance, request the publisher provide a documented privacy/data-retention policy or a self-hosting option. If any of these items are unacceptable, do not install or use the skill.

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 product photos in JPG format into a 1080p MP4"
• "turn my images into a smooth 15-second video with transitions"
• "converting static images into shareable video content for social media creators"

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.

AI Image to Video Creator — Convert Images 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 my images into a smooth 15-second video with 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 fewer images with higher resolution gives smoother motion results.

Matching Input to Actions

User prompts referencing ai image to video create, 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 <NEMO_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 ai-image-to-video-create, 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":"<lang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/<sid> — file: multipart -F "files=@/path", or URL: {"urls":["<url>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/<sid>/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_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/<id> 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 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=<id>, 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

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

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)

Common Workflows

Quick edit: Upload → "turn my images into a smooth 15-second 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn my images into a smooth 15-second 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.