Ai Image To Video Invideo

Skip the learning curve of professional editing software. Describe what you want — turn these images into a 30-second video with transitions and background m...

Security Scan

The skill’s declared purpose (convert images to videos) matches what its instructions do: it requires a NEMO_TOKEN and calls nemovideo.ai APIs to upload images, create sessions, and return rendered videos — there are no unrelated credentials or risky install steps.

Purpose & Capability

Name/description match the runtime instructions: the SKILL.md describes uploading images, creating sessions, SSE generation, export, and credit checks against mega-api-prod.nemovideo.ai. The only declared credential (NEMO_TOKEN) is directly relevant to the service.

Instruction Scope

Instructions are focused on the video-creation API endpoints and error handling. They also instruct the agent to read this skill file's YAML frontmatter at runtime and to detect the install path (~/.clawhub, ~/.cursor/skills/) to populate X-Skill-Platform; reading the skill's own frontmatter is reasonable, but runtime filesystem/installation-path inspection is broader than strictly required for an API client and should be noted.

Install Mechanism

No install spec and no code files — instruction-only skill. This is lowest-risk from an installation perspective (nothing is downloaded or written to disk by an installer).

Credentials

Only one environment credential is required (NEMO_TOKEN) and it is the primary credential for the described cloud service. The SKILL.md also describes obtaining an anonymous token if none is provided; no unrelated secrets or multi-service credentials are requested.

Persistence & Privilege

always is false and the skill does not request elevated platform-wide privileges. It does store session_id and tokens for API calls (normal for a client), and does not modify other skills or system-wide settings.

Assessment

This skill appears to do what it says: it will upload your images and use nemovideo.ai to render videos, so only install it if you trust that external service. Key things to consider before installing: 1) Privacy: uploaded images are sent to mega-api-prod.nemovideo.ai — review that service's privacy/billing policies if your images are sensitive. 2) Credentials: you can supply your NEMO_TOKEN or the skill will request an anonymous token on your behalf (100 free credits, 7-day expiry) — be aware the skill may create/use tokens automatically. 3) Local reads: the skill reads its own frontmatter and inspects install paths to populate attribution headers — this is limited access but worth noting. 4) Ask the publisher to clarify the small metadata inconsistency (SKILL.md frontmatter lists a config path ~/.config/nemovideo/ while the registry metadata listed none). If any of these behaviors are unacceptable, do not install.

Getting Started

Send me your images and I'll handle the AI video creation. Or just describe what you're after.

Try saying:

• "convert three product photos in JPG format into a 1080p MP4"
• "turn these images into a 30-second video with transitions and background music"
• "converting still images into shareable videos for marketers"

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 InVideo — Convert Images into Videos

Send me your images and describe the result you want. The AI video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload three product photos in JPG format, type "turn these images into a 30-second video with transitions and background music", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: using fewer images with longer durations per slide produces smoother results.

Matching Input to Actions

User prompts referencing ai image to video invideo, 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.

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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

• X-Skill-Source: ai-image-to-video-invideo
• 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":"<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 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=<id> (get <id> 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

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 → "turn these images into a 30-second video with transitions and background music" → Download MP4. Takes 1-2 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 "turn these images into a 30-second 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.