Image To Video Create Ai

Skip the learning curve of professional editing software. Describe what you want — turn these photos into a smooth video with transitions and background musi...

Security Scan

The skill’s behavior mostly matches an image→video cloud service, but there are inconsistencies about how credentials and config are handled and it will upload your files to an external backend you don't control — review before installing.

Purpose & Capability

The skill's name and description (convert images to video via cloud rendering) match the runtime instructions and endpoints. However, metadata and requirements are inconsistent: top-level metadata listed no config paths, but the skill frontmatter advertises ~/.config/nemovideo/; the registry requires NEMO_TOKEN yet the SKILL.md instructs the agent to automatically obtain an anonymous token if none is present. These mismatches reduce confidence in the manifest's accuracy.

Instruction Scope

Instructions are focused on uploading images and controlling render jobs via the nemovideo API, which is expected. They also instruct the agent to: read this SKILL.md frontmatter for attribution headers and detect its install path to populate a header (which implies reading local install path/metadata). While not clearly malicious, those file-system/agent-environment checks are beyond simple upload logic and should be noted. The skill will send user files and metadata to external endpoints (mega-api-prod.nemovideo.ai), which is necessary for cloud rendering but has privacy implications.

Install Mechanism

No install script or downloads are specified (instruction-only), so nothing is written to disk by the skill itself. This is the lowest-risk install mechanism.

Credentials

The skill declares a single primary credential (NEMO_TOKEN) which is appropriate for an external API. However, the SKILL.md instructs the agent to auto-request an anonymous token if NEMO_TOKEN is not present, which conflicts with the manifest claiming the env var is required. The frontmatter also references a config path (~/.config/nemovideo/) not present in the top-level registry metadata. These inconsistencies create ambiguity about what credentials or files the skill will read or create.

Persistence & Privilege

The skill is not always-enabled, does not include an install routine, and does not request system-wide configuration changes. It does require the agent to make outbound requests to the service, which is normal for a cloud-rendering skill.

What to consider before installing

This skill uploads your images and requests render jobs from an external service (mega-api-prod.nemovideo.ai). Before installing: 1) Confirm you trust that domain and the service's privacy policy — don't upload sensitive images unless you're comfortable they leave your device. 2) Note the manifest inconsistencies: the skill says NEMO_TOKEN is required but will also auto-create an anonymous token; decide whether you want the agent to request tokens on your behalf. 3) Ask the publisher for a homepage, privacy/terms links, and clarification on where anonymous tokens and any cached files are stored (the frontmatter references ~/.config/nemovideo/). 4) If you want tighter control, provide your own NEMO_TOKEN (only if you trust the service) or avoid installing the skill. Additional information that would raise confidence to benign: a known publisher/homepage, privacy policy, and consistent manifest fields (explicit config path and clear token-storage behavior).

Getting Started

Ready when you are. Drop your images here or describe what you want to make.

Try saying:

• "convert three product photos or a single landscape image into a 1080p MP4"
• "turn these photos into a smooth video with transitions and background music"
• "turning still images into shareable video content for marketers, social media creators, small business owners"

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 Creator — Convert Images Into Video Clips

Drop your 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 or a single landscape image, ask for turn these photos into a smooth video with transitions and background music, 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 create 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.

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":"<lang>"}. 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/<sid>	POST	Upload a file (multipart) or URL.
/api/credits/balance/simple	GET	Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latest	GET	Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda	POST	Start export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"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-create-ai
• 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 <NEMO_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=<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

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 photos into a smooth video with transitions and background music" — 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 devices.

Common Workflows

Quick edit: Upload → "turn these photos into a smooth video with transitions and background music" → 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.