Ai Video Generator From Image

Skip the learning curve of professional editing software. Describe what you want — turn this image into a 10-second animated video with smooth motion — and g...

Security Scan

The skill's requests and runtime instructions are consistent with an external AI video generation service — it only needs a single service token and makes API calls to nemovideo.ai — nothing in the bundle strongly contradicts its stated purpose.

Purpose & Capability

Name/description match the runtime instructions: the SKILL.md describes uploading images, creating a session, streaming SSE updates, and requesting renders from https://mega-api-prod.nemovideo.ai. The single required environment variable (NEMO_TOKEN) is directly tied to that API. Note: there is a minor metadata inconsistency — the registry summary lists no required config paths, but the SKILL.md frontmatter includes a configPaths value (~/.config/nemovideo/). This discrepancy should be clarified but does not by itself indicate misuse.

Instruction Scope

All runtime instructions focus on interacting with the remote rendering API (auth, session creation, upload, SSE, render/export). The SKILL.md instructs the agent to generate an anonymous token if NEMO_TOKEN is missing and to save session_id. One operational detail asks the agent to auto-detect an install path to populate X-Skill-Platform — that may require inspecting agent environment or paths. This is a modest scope expansion (reading an install path) but still related to providing correct request headers. The doc also instructs not to print tokens/raw JSON, which reduces risk of accidental disclosure.

Install Mechanism

Instruction-only skill with no install spec and no code files — lowest install risk. The skill relies on outbound HTTP calls to a named domain (nemovideo.ai); no downloads or archive extraction are specified.

Credentials

Only NEMO_TOKEN is required (primaryEnv). That single credential matches the stated purpose (API access to the rendering service). The SKILL.md also documents a flow to obtain an anonymous token, which is consistent with requiring the token. There are no requests for unrelated secrets or multiple credentials.

Persistence & Privilege

always is false and the skill does not request system-wide privileges. It instructs the agent to persist session_id and token usage for the session lifetime, which is reasonable for a remote rendering workflow. The skill does not ask to modify other skills or global agent settings.

Assessment

This skill is coherent with its description: it uploads images to an external service (nemovideo.ai) and needs a single API token (NEMO_TOKEN). Before installing, confirm you are comfortable with: (1) sending images to an external 3rd-party service and their data/retention/privacy policies; (2) storing an API token (the skill may persist a session token/session_id for job tracking); (3) the domain in the SKILL.md (mega-api-prod.nemovideo.ai) — verify it is the legitimate service you expect. Note the small metadata mismatch (the frontmatter lists a config path though the registry metadata did not); ask the publisher to clarify whether any files are written to ~/.config/nemovideo/. If you need stronger assurances, request the publisher provide a canonical homepage, documentation, or a vetted install release (or run the skill in a restricted/test environment first).

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:

• "turn my still images"
• "export 1080p MP4"
• "turn this image into a 10-second"

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.

AI Video Generator from Image — Turn Images into Video Clips

Send me your still 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 a single product photo or portrait image, type "turn this image into a 10-second animated video with smooth motion", 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 smoother motion results.

Matching Input to Actions

User prompts referencing ai video generator from image, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header	Value
X-Skill-Source	ai-video-generator-from-image
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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

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

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.

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

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 "turn this image into a 10-second animated video with smooth motion" — 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.

Common Workflows

Quick edit: Upload → "turn this image into a 10-second animated video with smooth motion" → 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.