Tiktok Photo Video Maker

Cloud-based tiktok-photo-video-maker tool that handles turning photo collections into short TikTok videos. Upload JPG, PNG, HEIC, WebP files (up to 200MB), d...

Security Scan

The skill's requirements and runtime instructions largely match its stated purpose (cloud TikTok-style video rendering), but there are a few small inconsistencies and privacy considerations you should review before installing.

Purpose & Capability

Name and description describe a cloud photo→video service. The skill only requests a single NEMO_TOKEN credential and directs network calls to a nemovideo.ai backend, which is coherent for a cloud-rendering service. Minor mismatch: the registry metadata listed no required config paths, but the SKILL.md frontmatter (metadata) references a config path (~/.config/nemovideo/).

Instruction Scope

SKILL.md instructs the agent to check NEMO_TOKEN, optionally obtain an anonymous token via POST to https://mega-api-prod.nemovideo.ai, create sessions, upload user files (multipart or URL), stream SSE, poll render status, and return download URLs. These actions are appropriate for a cloud render tool. Things to note: it reads environment variables and may detect install/config paths (~/.clawhub, ~/.cursor/skills/, ~/.config/nemovideo/), and will perform network requests to an external API. The instructions explicitly say not to expose tokens, which is appropriate.

Install Mechanism

There is no install spec and no code files (instruction-only). That minimizes on-disk risk; the skill operates via API calls only.

Credentials

Only one credential is required: NEMO_TOKEN (primaryEnv). That aligns with the described backend. The skill will create an anonymous token automatically if NEMO_TOKEN is absent. No unrelated secrets or multiple credentials are requested. However, the metadata's configPaths entry (~/.config/nemovideo/) appears in the frontmatter but the registry reported 'Required config paths: none' — this discrepancy should be clarified.

Persistence & Privilege

The skill does not request always:true and has no install behavior; session tokens are used at runtime and the skill appears to maintain only session-level state. It does not request system-wide configuration changes or cross-skill modifications.

Assessment

This skill appears to be what it says: a cloud service that uploads your images and returns a rendered TikTok-style MP4. Before installing, consider: (1) It will make network requests to mega-api-prod.nemovideo.ai and may automatically obtain an anonymous token if you don't supply NEMO_TOKEN — verify you trust that domain and service. (2) Uploaded images and audio are sent to a third party — review privacy and terms for sensitive content. (3) The SKILL.md references a config path (~/.config/nemovideo/) but the registry said none — ask the publisher which config is actually used. (4) Only provide NEMO_TOKEN if you trust it; do not supply other unrelated credentials. If you need higher assurance, ask the publisher for a homepage or source repository and confirm the API endpoints and token handling before use.

Getting Started

Share your photos and images and I'll get started on AI video creation. Or just tell me what you're thinking.

Try saying:

• "turn my photos and images"
• "export 1080p MP4"
• "turn my photos into a 30-second"

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.

TikTok Photo Video Maker — Turn Photos Into TikTok Videos

This tool takes your photos and images and runs AI video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have five product photos with a background music file and want to turn my photos into a 30-second TikTok video with transitions and music — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: vertical 9:16 aspect ratio is applied automatically for TikTok compatibility.

Matching Input to Actions

User prompts referencing tiktok photo video maker, 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.

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

Headers are derived from this file's YAML frontmatter. X-Skill-Source is tiktok-photo-video-maker, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).

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 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

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 30-second TikTok video with transitions and music" — concrete instructions get better results.

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

Export as MP4 for widest compatibility with TikTok and other social platforms.

Common Workflows

Quick edit: Upload → "turn my photos into a 30-second TikTok video with transitions and 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.