Youtube Generator Free

Turn a short blog post about travel tips into 1080p ready-to-upload videos just by typing what you need. Whether it's generating YouTube videos from text or...

Security Scan

The skill's behavior mostly matches a text→video service, but there are packaging inconsistencies (env/config declarations vs runtime instructions) and it will automatically obtain and store tokens and call an external API — review before installing.

Purpose & Capability

The skill's name/description (generate YouTube videos from text) aligns with the runtime instructions that call a remote rendering API (nemovideo.ai). However the registry metadata and the SKILL.md disagree: registry lists no config paths while the SKILL.md frontmatter declares configPaths (~/.config/nemovideo/) and requires.env lists NEMO_TOKEN even though the SKILL.md contains a full anonymous-token acquisition flow. These inconsistencies look like sloppy packaging rather than an immediate red flag, but they should be clarified.

Instruction Scope

The SKILL.md instructs only network interactions with the named backend (auth, session creation, SSE streaming, upload, render) and modest local checks (detecting install path for an attribution header). It does not instruct reading unrelated system credentials or scanning arbitrary files. It does instruct storing the anonymous token and session_id for subsequent requests and to avoid showing raw token values to the user.

Install Mechanism

No install spec or downloaded code is present (instruction-only), so nothing is written to disk by the skill itself. This is the lowest-risk install model.

Credentials

The only credential referenced is NEMO_TOKEN (declared as primary), which is consistent with a third-party video service. However, the SKILL.md describes acquiring an anonymous token itself if NEMO_TOKEN is not present, so marking NEMO_TOKEN as a required environment variable in registry metadata is misleading. The SKILL.md also references a config path (~/.config/nemovideo/) in its frontmatter that the registry metadata omitted — this mismatch should be resolved. No unrelated tokens or high-privilege env vars are requested.

Persistence & Privilege

The skill is not marked always:true and does not request elevated platform privileges. It will store an acquired token and session_id for its own use (normal for an API-backed skill). It also inspects install paths for attribution headers, which is low-privilege but should be noted.

What to consider before installing

This skill will contact https://mega-api-prod.nemovideo.ai, obtain and store an anonymous token (unless you pre-provide NEMO_TOKEN), create sessions, stream SSE responses, upload files, and return download URLs. The core functionality aligns with its description, but the package metadata and the instructions disagree about whether a NEMO_TOKEN/config path is required — ask the publisher to clarify. Before installing: (1) confirm you trust the nemovideo.ai service and the unknown skill author, (2) do not supply any unrelated secrets (AWS, GitHub, etc.), (3) be aware the skill will send your uploaded media and text to a third-party server, and (4) if you want stricter control, require manual consent before the skill auto-fetches tokens or uploads files. If you need higher assurance, request the publisher to fix the metadata inconsistencies and provide a privacy/terms link for the backend.

Getting Started

Send me your text or ideas and I'll handle the AI video generation. Or just describe what you're after.

Try saying:

• "generate a short blog post about travel tips into a 1080p MP4"
• "turn this text into a YouTube video with visuals and voiceover"
• "generating YouTube videos from text or ideas for free for YouTubers"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

YouTube Generator Free — Generate YouTube Videos From Text

Send me your text or ideas and describe the result you want. The AI video generation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a short blog post about travel tips, type "turn this text into a YouTube video with visuals and voiceover", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter scripts under 300 words generate faster and keep viewers engaged.

Matching Input to Actions

User prompts referencing youtube generator free, 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.

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

• X-Skill-Source: youtube-generator-free
• 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.

Error Codes

• 0 — success, continue normally
• 1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token
• 1002 — session not found; create a new one
• 2001 — out of credits; anonymous users get a registration link with ?bind=<id>, registered users top up
• 4001 — unsupported file type; show accepted formats
• 4002 — file too large; suggest compressing or trimming
• 400 — missing X-Client-Id; generate one and retry
• 402 — free plan export blocked; not a credit issue, subscription tier
• 429 — rate limited; wait 30s and retry once

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.

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 this text into a YouTube video with visuals and voiceover" → 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 "turn this text into a YouTube video with visuals and voiceover" — concrete instructions get better results.

Max file size is 200MB. Stick to MP4, MOV, TXT, DOCX for the smoothest experience.

Export as MP4 for widest compatibility with YouTube uploads.