Ai Image To Video Apk

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

Security Scan

The skill's requests and runtime instructions are consistent with an image→video cloud-rendering integration, but there is a small metadata mismatch and you should be aware that user files and an API token are sent to an external service.

Purpose & Capability

The skill claims to convert images to MP4 and only requests an API token (NEMO_TOKEN) and uses a cloud API for uploads/renders — this is proportional to its stated purpose. Minor inconsistency: SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata reported no required config paths.

Instruction Scope

Runtime instructions explicitly upload user images and exchange an anonymous or provided NEMO_TOKEN with the remote API; it tells the agent to create an anonymous token if none is present and to persist a session_id. These actions are necessary for the service, but they mean user files and generated tokens are transmitted to https://mega-api-prod.nemovideo.ai. The doc instructs not to print tokens or raw JSON, which helps limit accidental leaks. The skill also requires adding custom attribution headers on requests (X-Skill-Source/Version/Platform).

Install Mechanism

This is an instruction-only skill with no install spec or code to write to disk, which limits on-disk execution risk.

Credentials

Only one environment credential (NEMO_TOKEN) is declared as required and is appropriate for a cloud API. However, the frontmatter's configPaths entry (~/.config/nemovideo/) is inconsistent with the registry metadata (which listed none) and could indicate the skill expects local config files — SKILL.md does not clearly instruct reading that path. Confirm whether local config will be accessed.

Persistence & Privilege

The skill is not always-enabled and does not request elevated platform persistence. It does instruct saving a session_id and may store/keep the NEMO_TOKEN for the session period; this is normal for API-based skills.

Assessment

This skill uploads your images and uses an API token (NEMO_TOKEN) to render videos on https://mega-api-prod.nemovideo.ai. Before installing: (1) confirm you are comfortable with your images being sent to that external service and check its privacy terms; (2) verify whether the skill will store a generated anonymous token locally or in skill state and be prepared to revoke it if needed; (3) ask the publisher to clarify the configPaths inconsistency (~/.config/nemovideo/ appears in the SKILL.md frontmatter but was not declared in the registry) — ensure the skill will not read other local files; (4) avoid supplying any unrelated credentials. If you need higher assurance, request the skill author provide a clear statement about what local files (if any) are read/written and how long tokens/sessions are retained.

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 my photos 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.

AI Image to Video APK — Convert Images into MP4 Videos

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 three product photos or a single portrait image, type "turn my photos into a smooth animated video with transitions", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: using fewer images per video speeds up processing significantly.

Matching Input to Actions

User prompts referencing ai image to video apk, 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.

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

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

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

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 "turn my photos into a smooth animated 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.

Common Workflows

Quick edit: Upload → "turn my photos into a smooth animated 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.