Ai Image To Video Effects

Skip the learning curve of professional editing software. Describe what you want — animate this image with a cinematic zoom and motion blur effect — and get...

Security Scan

The skill's behavior mostly matches an image→video service (uses a single NEMO_TOKEN and remote API calls), but there are small inconsistencies (declared vs. in-file metadata) and several runtime behaviors that you should verify before trusting it with credentials or private images.

Purpose & Capability

The name/description align with the runtime instructions: the skill uploads images and drives a remote render pipeline. Requiring NEMO_TOKEN as the primary credential is consistent. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the provided registry metadata said no config paths; this mismatch is an incoherence worth questioning (does the skill expect to read local Nemovideo config files?).

Instruction Scope

Instructions are focused on connecting to the remote API, creating sessions, uploading media, reading SSE, and returning download URLs. They also instruct the agent to read the skill's frontmatter and to detect the agent install path (~/.clawhub/, ~/.cursor/skills/) to set X-Skill-Platform — which implies filesystem queries beyond pure network calls. No instructions request unrelated system credentials or to exfiltrate arbitrary files, but the install-path detection and frontmatter reading are behaviors you should be aware of.

Install Mechanism

This is an instruction-only skill with no install spec and no code files, so nothing is downloaded or written to disk by an installer. That minimizes install-time risk.

Credentials

Only one credential is declared (NEMO_TOKEN) which fits the described API use. The SKILL.md also documents generating an anonymous token if none is present. The earlier registry metadata claiming no configPaths conflicts with the SKILL.md frontmatter that lists ~/.config/nemovideo/ — this could imply additional local config access not declared at the registry level.

Persistence & Privilege

always:false and normal autonomous invocation are used. The skill does not request permanent system-wide presence or to modify other skills' configs.

What to consider before installing

This skill appears to do what it says (drive a remote Nemovideo rendering API) and only needs a single token, but there are a few things to check before installing or using it: 1) Confirm the backend domain (mega-api-prod.nemovideo.ai) and the vendor — there's no homepage or source provided. 2) Ask the author why SKILL.md lists a local config path (~/.config/nemovideo/) while the registry metadata does not; if the skill will attempt to read that directory, understand what it will look for. 3) If you don't want to provide a long-lived NEMO_TOKEN, use the anonymous-token flow but be aware those tokens have limited credits and lifetime. 4) The skill will inspect install paths and its own frontmatter to set attribution headers — this requires filesystem access; if you run in a context where that access is sensitive, restrict the skill or review its runtime environment. 5) Because uploads are sent to a third-party GPU service, avoid uploading sensitive images unless you’ve verified the provider’s privacy/retention policy. If you need higher assurance, request the author publish a source repo, a vendor site, or documentation clarifying the configPath usage and backend ownership.

Getting Started

Got still images to work with? Send it over and tell me what you need — I'll take care of the AI video effects generation.

Try saying:

• "convert a single product photo or landscape image into a 1080p MP4"
• "animate this image with a cinematic zoom and motion blur effect"
• "turning static images into animated video clips with motion effects for social media creators, marketers, photographers"

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 Effects — Animate Images Into Video Clips

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

A quick example: upload a single product photo or landscape image, type "animate this image with a cinematic zoom and motion blur effect", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: high-contrast images with clear subjects produce the most noticeable motion effects.

Matching Input to Actions

User prompts referencing ai image to video effects, 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: ai-image-to-video-effects
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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.

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 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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "animate this image with a cinematic zoom and motion blur effect" — 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 → "animate this image with a cinematic zoom and motion blur effect" → 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.