Dzine Ai

create images or prompts into designed video content with this dzine-ai skill. Works with JPG, PNG, MP4, MOV files up to 200MB. marketers use it for turning...

Security Scan

The skill's requests and runtime instructions are largely consistent with a cloud video-rendering integration (it needs a NEMO_TOKEN and calls nemo API endpoints), but there are a few small inconsistencies and behavior notes worth reviewing before installing.

Purpose & Capability

The skill claims to create/transform images into video via a remote service and requires a single service credential (NEMO_TOKEN). That aligns with the stated purpose. Minor inconsistency: the SKILL.md frontmatter metadata references a config path (~/.config/nemovideo/) and install-path detection, whereas the registry metadata reported no required config paths — this is a small mismatch but explainable (the skill may optionally read its own config).

Instruction Scope

Runtime instructions stay within the video-rendering domain (session creation, SSE, uploads, export polling). The skill will automatically obtain an anonymous token if NEMO_TOKEN is not present (POST to an anonymous-token endpoint) and will store session_id/token for subsequent calls. It also instructs reading its YAML frontmatter and probing install paths to set attribution headers. These behaviors are reasonable for operation, but they do involve creating/storing a token and reading some local paths (install location and possibly ~/.config/nemovideo/) which the user should be aware of.

Install Mechanism

Instruction-only skill with no install spec and no code files — nothing is written to disk by an installer. Lowest-risk installation footprint.

Credentials

Only one credential is requested (NEMO_TOKEN), which is proportional to a cloud-rendering service. The SKILL.md does describe generating and storing an anonymous token if none is supplied. The embedded metadata's reference to a config path (~/.config/nemovideo/) is not declared in the registry requirements, which is a minor inconsistency to confirm.

Persistence & Privilege

The skill is not always-enabled, and autonomous model invocation remains default (allowed). It stores session_id/token for the session as part of normal operation but does not request elevated platform privileges or modify other skills. No excessive persistence flags are present.

Assessment

This skill appears to do what it says: call nemo video APIs to render videos and therefore needs a NEMO_TOKEN. Before installing, consider: 1) Provide your own NEMO_TOKEN if you have one (safer than relying on automatically minted anonymous tokens). 2) The skill will call external endpoints (mega-api-prod.nemovideo.ai) and will create and store a session token — verify you are okay with that service receiving uploaded media. 3) The SKILL.md mentions reading install paths and a config directory (~/.config/nemovideo/) — ask the publisher whether and how local files or that folder are accessed. 4) If you handle sensitive media, review the service's privacy/data-retention policies. If you need certainty about the minor metadata inconsistency or where tokens/sessions are persisted, request clarification from the skill author before enabling it.

Getting Started

Ready when you are. Drop your images or prompts here or describe what you want to make.

Try saying:

• "create three product photos and a brand color hex code into a 1080p MP4"
• "turn my product images into a branded promotional video with motion effects"
• "turning static images into animated branded videos for marketers"

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.

Dzine AI — Create AI-designed video content

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

A quick example: upload three product photos and a brand color hex code, type "turn my product images into a branded promotional video with motion effects", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: using fewer images per scene speeds up render time significantly.

Matching Input to Actions

User prompts referencing dzine ai, 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.

Skill attribution — read from this file's YAML frontmatter at runtime:

• X-Skill-Source: dzine-ai
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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.

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.

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)

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn my product images into a branded promotional video with motion effects" — concrete instructions get better results.

Max file size is 200MB. Stick to JPG, PNG, MP4, MOV for the smoothest experience.

Export as MP4 for widest compatibility across social platforms.

Common Workflows

Quick edit: Upload → "turn my product images into a branded promotional video with motion effects" → Download MP4. Takes 1-2 minutes 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.