Youtube Ai Video Maker

Skip the learning curve of professional editing software. Describe what you want — turn my footage into a YouTube-ready video with intro, cuts, and music — a...

Security Scan

The skill's behavior mostly matches a cloud video-editing integration, but there are mismatches and minor scope creep (local config/install-path access and metadata inconsistencies) and no upstream source or homepage to validate the service.

Purpose & Capability

The name/description (YouTube AI video maker) aligns with the runtime instructions to upload clips and call a cloud render API; requiring a NEMO_TOKEN is consistent. However the SKILL.md metadata references a local config path (~/.config/nemovideo/) and install-path detection that aren't declared in the registry metadata — an inconsistency to question.

Instruction Scope

Instructions direct the agent to upload user video files to https://mega-api-prod.nemovideo.ai, manage sessions, poll SSE endpoints, and include Authorization headers. They also instruct the agent to read the skill file's YAML frontmatter for attribution and to detect installation path (e.g., ~/.clawhub/ or ~/.cursor/skills/) — both require reading local filesystem state beyond simply handling user-uploaded media. This is scope creep worth confirming with the publisher.

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 reduces installation risk.

Credentials

Only NEMO_TOKEN is requested as the primary credential, which fits a cloud API. The SKILL.md also describes acquiring an anonymous token via the external API if NEMO_TOKEN is absent. The SKILL.md mentions a config path (~/.config/nemovideo/) not declared in the registry metadata — request this discrepancy be clarified.

Persistence & Privilege

The skill is not marked 'always:true' and doesn't request elevated/system-wide persistence. It does ask to detect install path and read local config, but it does not request to modify other skills or system settings.

What to consider before installing

This skill appears to be a client for a cloud video-rendering service (mega-api-prod.nemovideo.ai). Before installing: 1) Confirm you trust that external domain and review its privacy/retention policy—you will be uploading video files and the skill will send Authorization headers (NEMO_TOKEN) to that service. 2) Ask the publisher to explain the registry metadata mismatch: SKILL.md references ~/.config/nemovideo/ and install-path detection but the registry metadata did not list config paths. 3) Understand that if you don't provide NEMO_TOKEN the skill will request an anonymous token from the remote API (network call). 4) Because this is instruction-only (no code to audit) and the source/homepage are missing, prefer using a short-lived or limited token and avoid uploading sensitive footage until you verify the service. 5) If you need higher assurance, request the skill's source or a homepage and a privacy statement from the owner.

Getting Started

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

Try saying:

• "create a 10-minute raw YouTube vlog recording into a 1080p MP4"
• "turn my footage into a YouTube-ready video with intro, cuts, and music"
• "generating polished YouTube videos from raw footage using AI for YouTubers"

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.

YouTube AI Video Maker — Create and Export YouTube Videos

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

Say you have a 10-minute raw YouTube vlog recording and want to turn my footage into a YouTube-ready video with intro, cuts, and music — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter source clips under 5 minutes process significantly faster and yield tighter edits.

Matching Input to Actions

User prompts referencing youtube ai 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.

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

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

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

SSE Event Handling

Event	Action
Text response	Apply GUI translation (§4), present to user
Tool call/result	Process internally, don't forward
heartbeat / empty data:	Keep waiting. Every 2 min: "⏳ Still working..."
Stream closes	Process final response

~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn my footage into a YouTube-ready video with intro, cuts, and music" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for the best balance of quality and YouTube upload compatibility.

Common Workflows

Quick edit: Upload → "turn my footage into a YouTube-ready video with intro, cuts, and music" → 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.