Ai Video Maker From Photo

Skip the learning curve of professional editing software. Describe what you want — turn these photos into a slideshow video with transitions and background m...

Security Scan

This instruction-only skill is internally consistent with its purpose: it uploads photos to a nemovideo.ai backend using a single NEMO_TOKEN (or an anonymous token it obtains) to render videos; it does not request unrelated credentials or install arbitrary code.

Purpose & Capability

Name/description (turn photos into MP4s) align with the actions in SKILL.md: uploading images, creating render sessions, polling render status, and downloading a video. The primary credential (NEMO_TOKEN) and the API host (mega-api-prod.nemovideo.ai) are consistent with the described cloud rendering service. Minor inconsistency: the skill's YAML frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata provided to you earlier listed no required config paths — this is likely a metadata mismatch rather than a functional red flag, but it should be noted.

Instruction Scope

Instructions are concrete and limited to interacting with the remote rendering API (session creation, SSE, upload, export, polls). The runtime will send user images and request/response data to the nemovideo.ai endpoints — expected for this service, but it does mean user files and metadata will leave the local machine. The skill also instructs the agent to look for NEMO_TOKEN and to detect install path for X-Skill-Platform header; it does not instruct reading unrelated system files or other env vars.

Install Mechanism

No install spec and no code files (instruction-only). This is the lowest-risk install model: nothing is downloaded or written by the skill itself.

Credentials

Only one credential is requested: NEMO_TOKEN (declared as primaryEnv). That is proportional to a cloud-rendering service. The skill also implements an anonymous-token fallback flow (POST to the service to obtain a short-lived token) which explains why an env var is optional in practice. Note the small metadata mismatch: the SKILL.md frontmatter also declares a config path (~/.config/nemovideo/) not present in the registry's required config paths — likely benign but inconsistent.

Persistence & Privilege

always is false and the skill is user-invocable; it does not request permanent platform-wide privileges. The skill instructs the agent to store session_id for the session lifecycle, which is reasonable for a rendering workflow.

Assessment

This skill will send any photos you upload to the nemovideo.ai backend and use a NEMO_TOKEN for authorization. If you set NEMO_TOKEN in your environment, that token will be used; if not, the skill will request a short-lived anonymous token from https://mega-api-prod.nemovideo.ai and use that. Before installing or using the skill: 1) Do not upload sensitive/private images unless you trust the nemovideo.ai service and its privacy terms; 2) Be aware that setting a global NEMO_TOKEN means that token will be used by this skill — only provide a token you intend to share with the service; 3) Note the SKILL.md frontmatter mentions a config path (~/.config/nemovideo/) although the registry metadata did not — this is likely a harmless metadata mismatch but consider verifying expected config/storage behavior; 4) Because this is instruction-only, no code is installed locally, but network activity will occur to the specified API host. If you need more assurance, request the maintainer/source or check the service's privacy policy before uploading private content.

Getting Started

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

Try saying:

• "turn five vacation photos in JPG format into a 1080p MP4"
• "turn these photos into a slideshow video with transitions and background music"
• "turning photo collections into shareable videos for social media creators, marketers"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

• Generate a UUID as client identifier
• POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
• Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

AI Video Maker from Photo — Turn Photos into MP4 Videos

Send me your photos or 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 five vacation photos in JPG format, type "turn these photos into a slideshow video with transitions and background music", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: using 5-10 photos gives the best pacing for short social videos.

Matching Input to Actions

User prompts referencing ai video maker from photo, 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-video-maker-from-photo
• 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.

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 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 → "turn these photos into a slideshow video with transitions and background music" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn these photos into a slideshow video with transitions and background music" — 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.