Ai Image To Video Animation

Turn a single product photo or illustrated scene into 1080p animated video clips just by typing what you need. Whether it's turning static images into short...

Security Scan

The skill's requests and runtime instructions are largely consistent with an image→video cloud-rendering integration, with only minor inconsistencies (metadata vs registry) and a few design choices you should review before installing.

Purpose & Capability

The skill's name/description (convert images to animated videos) aligns with the declared primary credential (NEMO_TOKEN) and the API endpoints referenced in SKILL.md. Requesting a token for the external nemo video service is expected for this purpose. Minor inconsistency: the top-level registry said no required config paths, but the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) — plausible for storing session state but inconsistent with the registry metadata.

Instruction Scope

SKILL.md is instruction-only and describes the exact API calls to perform (anonymous token acquisition, session creation, SSE streaming, upload, export polling). These actions stay within the stated purpose. The instructions do ask the agent to detect an install path (~/.clawhub/, ~/.cursor/skills/) to set an X-Skill-Platform header and to store session/token values for subsequent requests — both are implementation details that require filesystem and environment access; they are not strictly harmful but expand the scope beyond purely 'upload/convert/download'.

Install Mechanism

No install spec and no code files — instruction-only skill. This is lower risk because nothing is written to disk by an install step. All runtime behavior comes from the SKILL.md instructions.

Credentials

Only NEMO_TOKEN is declared as required and is used by the API calls; SKILL.md also supports auto-obtaining an anonymous token if NEMO_TOKEN is not present. No unrelated secrets or multiple credentials are requested. The single-env requirement is proportionate to the stated cloud-rendering purpose.

Persistence & Privilege

The skill instructs storing the anonymous/returned token and session_id for subsequent requests, which is expected for a session-based API. always:false (no forced global inclusion). This storage and reuse is normal for the service but you should be aware the skill will retain a session token and may use it for subsequent network calls.

Assessment

This skill appears to do what it says: it talks to an external NemoVideo API to turn images into videos and needs a NEMO_TOKEN (or will request an anonymous one). Before installing, consider: (1) Do you trust the endpoint (https://mega-api-prod.nemovideo.ai)? the skill will make network calls and may store a session token locally. (2) If you prefer control, set your own NEMO_TOKEN in the environment rather than letting the skill request an anonymous token. (3) The SKILL.md mentions detecting install paths and a config directory (~/.config/nemovideo/) — review where session/tokens will be stored on your system and clear them if needed. (4) Monitor network activity and avoid granting the agent broader autonomous privileges if you don’t trust the service. If you want more assurance, ask the skill author for a privacy/storage policy or for explicit details about where tokens and generated media are saved.

Getting Started

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

Try saying:

• "convert my still images"
• "export 1080p MP4"
• "animate this image into a 5-second"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

AI Image to Video Animation — Convert Images Into Animated Videos

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

Say you have a single product photo or illustrated scene and want to animate this image into a 5-second video with smooth motion — the backend processes it in about 30-90 seconds and hands you a 1080p MP4.

Tip: high-contrast images with clear subjects produce the most fluid animations.

Matching Input to Actions

User prompts referencing ai image to video animation, 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-animation, 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

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "animate this image into a 5-second video with smooth motion" — concrete instructions get better results.

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

PNG images with clean backgrounds give the AI more accurate motion results.

Common Workflows

Quick edit: Upload → "animate this image into a 5-second video with smooth motion" → Download MP4. Takes 30-90 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.