Video Maker Free Ai App

create video clips or images into polished MP4 videos with this skill. Works with MP4, MOV, JPG, PNG files up to 500MB. TikTok creators and small business ow...

Security Scan

The skill's claimed purpose (remote AI video creation) matches the actions and the single requested credential (NEMO_TOKEN); nothing in the instructions asks for unrelated secrets or system access, though a small metadata mismatch is worth noting.

Purpose & Capability

The skill name/description and the SKILL.md consistently describe a cloud-based video render pipeline. The only required environment variable is NEMO_TOKEN, which is appropriate for authenticating to the described API endpoints. The endpoints, upload, session, credits, and render flows all align with the stated video creation purpose.

Instruction Scope

Runbook instructs the agent to create sessions, upload user media, stream SSE, poll job status, and return download URLs — all expected for a remote render service. It explicitly requires Authorization and attribution headers. One minor inconsistency: the metadata lists a configPath (~/.config/nemovideo/) but the runtime instructions do not explain reading that path; it's unclear whether the agent will read local config files.

Install Mechanism

This is instruction-only with no install spec and no code files, so nothing is written to disk by an installer. That is the lowest-risk install profile and matches the described cloud-based operation.

Credentials

The skill requests a single credential (NEMO_TOKEN) which is consistent with authenticating to the vendor API; the SKILL.md also provides a fallback anonymous-token flow if no token is present. The metadata's declared configPath (~/.config/nemovideo/) is unexpected relative to the instructions and could imply local config access; the file instructions do not show reading any other env vars or secrets.

Persistence & Privilege

always is false and the skill does not request elevated or persistent system privileges. It does not instruct modifying other skills or global agent settings. Model invocation is allowed (normal) but that combined with this skill's limited scope does not raise a privilege concern.

Assessment

This skill appears internally consistent for a cloud video-rendering service. Before installing or using it: 1) Confirm you trust the remote domain (mega-api-prod.nemovideo.ai) because uploaded media and generated tokens are sent there. 2) Avoid uploading sensitive personal or corporate videos unless you understand the provider's privacy and retention policy. 3) The skill will accept a NEMO_TOKEN or obtain an anonymous token for you — prefer supplying a token from an account you control if you want better access tracking. 4) Ask the skill author what the listed config path (~/.config/nemovideo/) is used for; if it reads local config files, that should be documented and justified. 5) If you need higher assurance, request a verified homepage or vendor documentation before installing.

Getting Started

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

Try saying:

• "create five product photos and a background music file into a 1080p MP4"
• "turn my photos into a 30-second promo video with transitions and text"
• "creating short videos from photos or clips without editing software for TikTok creators and small business owners"

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.

Video Maker Free AI App — Create and Export AI Videos

Send me your video clips 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 product photos and a background music file, type "turn my photos into a 30-second promo video with transitions and text", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: shorter clips under 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing video maker free ai app, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint	Method	Purpose
/api/tasks/me/with-session/nemo_agent	POST	Start a new editing session. Body: {"task_name":"project","language":"<lang>"}. Returns session_id.
/run_sse	POST	Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/<sid>	POST	Upload a file (multipart) or URL.
/api/credits/balance/simple	GET	Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latest	GET	Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda	POST	Start export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

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

Header	Value
X-Skill-Source	video-maker-free-ai-app
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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.

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

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)

Common Workflows

Quick edit: Upload → "turn my photos into a 30-second promo video with transitions and text" → 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 my photos into a 30-second promo video with transitions and text" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across social platforms.