Ai Image To Video Easemate

convert still images into animated video clips with this skill. Works with JPG, PNG, WEBP, HEIC files up to 200MB. social media creators use it for convertin...

Security Scan

The skill's requirements and runtime instructions are consistent with an image→video cloud render service, but there are a few minor inconsistencies and privacy/visibility considerations you should review before installing.

Purpose & Capability

The skill claims to convert images to videos and only requests a single service credential (NEMO_TOKEN) and network access to nemovideo.ai endpoints, which is proportional to that purpose.

Instruction Scope

SKILL.md instructs the agent to use an existing NEMO_TOKEN or obtain an anonymous token by POSTing to the vendor API, create sessions, upload files, stream SSE, and poll render status — all expected for a cloud render pipeline. It also instructs the agent to 'keep technical details out of the chat' (which hides backend activity from users) and to detect an install path (e.g., ~/.clawhub/, ~/.cursor/skills/) to set an X-Skill-Platform header, which implies looking at local paths. Those filesystem checks and the explicit instruction to hide technical details are worth noting since they expand what the agent will read/do beyond only sending images.

Install Mechanism

This is an instruction-only skill with no install spec or downloadable artifacts, so nothing is written to disk by an installer — lower risk from an install perspective.

Credentials

Only one environment variable is declared (NEMO_TOKEN) which is appropriate for an API-backed renderer. However, the SKILL.md YAML metadata references a config path (~/.config/nemovideo/) while the registry summary earlier lists no required config paths — this mismatch should be clarified. The anonymous-token flow is documented and yields a short-lived token, which reduces the need to supply a long-lived secret.

Persistence & Privilege

The skill is not force-included (always: false) and does not request persistent system privileges. It does describe reading standard install/config paths and creating sessions with the remote service, but it does not ask to alter other skills or system-wide settings.

Assessment

This skill appears to do what it says: upload your images to nemovideo.ai and return rendered MP4s. Before installing or giving it a token, consider: (1) Privacy — your images (and any metadata) will be uploaded to the vendor's cloud; avoid sensitive content unless you trust the service and have reviewed its terms. (2) Token scope — prefer using a limited/anonymous token rather than a long-lived production token; the skill can obtain a 7-day anonymous token if none is present. (3) Local file access — the instructions ask the agent to detect install/config paths (e.g., ~/.clawhub/, ~/.cursor/, ~/.config/nemovideo/) which means the agent may read those locations; if you are uncomfortable, do not allow that. (4) Inconsistency — metadata in the SKILL.md mentions a config path, but the registry summary said none; ask the publisher to confirm what local paths are accessed. (5) Verify endpoint legitimacy (mega-api-prod.nemovideo.ai) and vendor policies before uploading content. If you need higher assurance, request the skill author to clarify the config-path usage, to remove instructions that hide backend activity from users, and to document exactly what local files (if any) will be read.

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"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

• Generate a UUID as client identifier
• POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
• The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

AI Image to Video EaseMate — Convert Images into Videos

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 these images 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 fewer images per video speeds up processing time noticeably.

Matching Input to Actions

User prompts referencing ai image to video easemate, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is ai-image-to-video-easemate, 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).

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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

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.

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

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 images 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 platforms and devices.

Common Workflows

Quick edit: Upload → "turn these images 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.