Create Image To Video Ai

Skip the learning curve of professional editing software. Describe what you want — turn these images into a smooth 15-second video with transitions — and get...

Security Scan

The skill's requirements and runtime instructions are consistent with an image→video cloud rendering service; it asks only for a service token and uses API endpoints to upload images and request renders.

Purpose & Capability

Name, description, and required credential (NEMO_TOKEN) align with a cloud image-to-video rendering service. The skill's declared API endpoints and upload/export flows are consistent with that purpose. Minor inconsistency: the SKILL.md frontmatter mentions a config path (~/.config/nemovideo/) while the registry metadata lists no required config paths.

Instruction Scope

Instructions are narrowly focused on creating a session, uploading files, using SSE for interactive edits, and exporting a video. They do instruct generating an anonymous token via an external POST and storing a session_id. The SKILL.md also describes deriving X-Skill-Platform from the install path (e.g., checking ~/.clawhub), which implies reading local install path(s) or environment to set headers — this is not strictly necessary for core functionality and should be noted by users who care about local path exposure.

Install Mechanism

No install spec or code files are present (instruction-only), so nothing is downloaded or written by an installer. This is the lowest-risk install profile.

Credentials

Only one environment variable (NEMO_TOKEN) is required, which is proportional to a cloud API integration. The SKILL.md also references a config path (~/.config/nemovideo/) in its metadata; if the agent actually reads that path it could access locally stored tokens or config — this is plausible for convenience but is additional filesystem access beyond just reading NEMO_TOKEN from env.

Persistence & Privilege

The skill is not always-included and has no install persistence; it does request creating and saving a session_id for ongoing jobs, which is normal for remote render sessions. Autonomous invocation is allowed (platform default) but not combined with other high-risk requests.

Assessment

This skill appears to do what it says: upload your images to a third‑party rendering service and return a video. Before installing or using it, consider: (1) it requires a NEMO_TOKEN (or will request an anonymous token) — that token grants access to the external API, so treat it as a secret; (2) images you upload are sent to https://mega-api-prod.nemovideo.ai — do not upload sensitive or private images you wouldn’t want processed by an external service; (3) the SKILL.md mentions a local config path (~/.config/nemovideo/) and deriving a platform header from an install path — if you are privacy-conscious, confirm whether your agent will actually read that path or only use environment vars; (4) anonymous tokens are short-lived (100 credits, 7 days) per the doc; if you expect longer or private use, obtain an appropriate token from the service. The skill is internally coherent, but verify the external domain and token handling before proceeding.

Getting Started

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

Try saying:

• "convert my still images"
• "export 1080p MP4"
• "turn these images into a smooth"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Create Image to Video AI — Turn 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 three product photos in JPG format and want to turn these images into a smooth 15-second video with transitions — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: using fewer images with higher resolution produces smoother motion output.

Matching Input to Actions

User prompts referencing create image to video 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 <NEMO_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 create-image-to-video-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":"<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 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 → "turn these 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 these 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.