Ai Product Video

Turn three product photos and a logo into 1080p polished product videos just by typing what you need. Whether it's creating product showcase videos from phot...

Security Scan

The skill's requests and runtime instructions are consistent with a remote video-rendering service and only require a single service token (NEMO_TOKEN); nothing in the instructions suggests access to unrelated credentials or system resources beyond small, expected metadata reads.

Purpose & Capability

The skill is described as a cloud-based product-photo→video service and its runtime instructions call a remote API, upload user images, create render jobs, and return download URLs. Requiring a single NEMO_TOKEN credential (or obtaining an anonymous token) is coherent with that purpose. Minor inconsistency: the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) in its metadata, but the registry metadata shows no required config paths; this mismatch should be clarified but does not by itself indicate malicious intent.

Instruction Scope

Instructions focus on authenticating, session creation, SSE streaming, uploads, and polling export status—all within the scope of a render service. The skill instructs reading its own frontmatter (for version) and detecting install path to populate X-Skill-Platform headers; these are limited metadata reads but do require the agent to inspect its environment. The instructions do not direct reading arbitrary user files or other credentials beyond NEMO_TOKEN.

Install Mechanism

This is an instruction-only skill with no install spec and no code files, so nothing is written to disk by an installer. That is the lowest-risk install model.

Credentials

Only one credential is declared (NEMO_TOKEN) and the SKILL.md uses it for Bearer auth to the documented API. If NEMO_TOKEN is absent the skill requests an anonymous token from the backend (no additional credentials requested). The only minor concern is the frontmatter's mention of a config path (~/.config/nemovideo/) which could contain tokens; registry metadata did not declare any config paths—this discrepancy should be resolved.

Persistence & Privilege

The skill is not always-enabled and does not request system-wide persistence. It does not instruct modification of other skills or global agent settings. Autonomous invocation is allowed but that is the platform default and not in itself a reason to flag the skill.

Assessment

What to consider before installing: - This skill uploads user images and a token to an external API at mega-api-prod.nemovideo.ai. Confirm you trust that domain and its privacy/retention policy before sending sensitive images. - The skill expects a NEMO_TOKEN; only provide a token scoped to this service. Prefer a limited or throwaway token if you want to reduce risk. - The SKILL.md frontmatter references a config path (~/.config/nemovideo/) but the registry lists no required config paths — ask the publisher to clarify whether the skill will read local config files and why. - Because this is an instruction-only skill, it will make network calls at runtime. If you have network-monitoring or proxy controls, consider using them to inspect outgoing requests during first use. - If you need higher assurance, request the publisher's homepage or source repo (none provided) and verify the API endpoints and behavior there. If anything looks unexpected, revoke any token you provided and remove the skill.

Getting Started

Send me your product images and I'll handle the AI video creation. Or just describe what you're after.

Try saying:

• "create three product photos and a logo into a 1080p MP4"
• "create a 30-second product showcase video with background music and text overlays"
• "creating product showcase videos from photos for e-commerce listings for e-commerce sellers and marketers"

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 Product Video — Turn Product Photos Into Videos

Send me your product 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 and a logo, type "create a 30-second product showcase video with background music and text overlays", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: using a plain or white background in your product photos gives the AI cleaner results.

Matching Input to Actions

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

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

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.

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)

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

Common Workflows

Quick edit: Upload → "create a 30-second product showcase video with background music and text overlays" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "create a 30-second product showcase video with background music and text overlays" — concrete instructions get better results.

Max file size is 500MB. Stick to JPG, PNG, MP4, MOV for the smoothest experience.

Export as MP4 for widest compatibility across Amazon, Shopify, and social platforms.