Youtube Video Free

edit video clips into YouTube-ready videos with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. YouTubers use it for editing and exporting free...

Security Scan

The skill's requests and runtime instructions are generally consistent with a cloud-based video editing service, but there are small metadata inconsistencies and privacy/third‑party upload implications you should be aware of before installing.

Purpose & Capability

The skill claims to be a cloud video editor and all required items (Bearer token NEMO_TOKEN, API endpoints, session flow) align with that purpose. However, the SKILL.md frontmatter declares a required config path (~/.config/nemovideo/) while the registry metadata above lists no required config paths — this mismatch should be reconciled.

Instruction Scope

Instructions stay within a video-editing scope: authenticate, create a session, upload media, use SSE for edits, and request renders. Important runtime behaviors: it will upload user video files to the remote backend (privacy/consent/billing implication), generate an anonymous token if no NEMO_TOKEN provided, and determine skill attribution by inspecting the skill frontmatter and install path (implies reading install location). There is no instruction to read unrelated system files or other credentials.

Install Mechanism

No install spec and no code files (instruction-only) — nothing will be written to disk by an installer. This is the lowest-risk class of skill for installation footprint.

Credentials

Only NEMO_TOKEN is required as a credential, which is appropriate for a service that performs server-side rendering. The SKILL.md also references a config path (~/.config/nemovideo/) in its metadata while the registry metadata omitted it — this inconsistency is suspicious but not necessarily malicious. No unrelated secrets or multiple credentials are requested.

Persistence & Privilege

always is false and the skill does not request persistent, elevated privileges or modifications to other skills. It does not attempt to persist tokens locally in any installation step (no installer present). Autonomous invocation is allowed (platform default) but not combined with other high-risk factors here.

Assessment

This skill appears to be a straightforward cloud-based video editing integration that uploads your media to mega-api-prod.nemovideo.ai and requires a NEMO_TOKEN (or will request an anonymous token). Before installing or using it: 1) Confirm you trust the remote service and its privacy/billing terms — your raw video files are uploaded to their servers. 2) Prefer providing a token from a trusted account rather than relying on anonymous tokens if you need accountability. 3) Note the metadata mismatch: SKILL.md mentions ~/.config/nemovideo/ while the registry metadata does not — ask the publisher to clarify what local config (if any) the skill expects. 4) Because this is instruction-only, no local code is installed, but the agent will make network calls to a third‑party API; only proceed if you are comfortable with that data flow.

Getting Started

Send me your video clips and I'll handle the AI video editing. Or just describe what you're after.

Try saying:

• "edit a 3-minute YouTube vlog recording into a 1080p MP4"
• "trim the intro, add subtitles, and export for YouTube upload"
• "editing and exporting free YouTube videos without paid software 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 Video Free — Edit and Export YouTube Videos Free

Send me your video clips and describe the result you want. The AI video editing runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 3-minute YouTube vlog recording, type "trim the intro, add subtitles, and export for YouTube upload", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 2 minutes process significantly faster and use fewer credits.

Matching Input to Actions

User prompts referencing youtube video 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-video-free
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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 → "trim the intro, add subtitles, and export for YouTube upload" → 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 "trim the intro, add subtitles, and export for YouTube upload" — 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 compatibility with YouTube uploads.