Youtube Video Editor Remastered

Turn a 10-minute unedited YouTube vlog recording into 1080p polished edited clips just by typing what you need. Whether it's re-editing and enhancing existin...

Security Scan

The skill's instructions and requirements generally match its stated purpose (cloud video editing), with a few minor inconsistencies in metadata and how a token is obtained that the user should understand before installing.

Purpose & Capability

The skill is a cloud video editor and only requests a single service token (NEMO_TOKEN) which aligns with that purpose. Minor inconsistency: the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata declared no required config paths; also the skill declares NEMO_TOKEN as required/primary even though the instructions include an anonymous-token fallback.

Instruction Scope

Runtime instructions focus on uploading media, creating sessions, streaming edits, polling renders, and returning download URLs from the nemovideo backend. The instructions do not direct reading unrelated local files or unrelated environment secrets. They do instruct reading the skill's own frontmatter and the agent install path to form attribution headers.

Install Mechanism

This is instruction-only (no install spec, no code files). No downloads or archive extraction are specified, which minimizes install-time risk.

Credentials

The only declared secret is NEMO_TOKEN, which is appropriate for a cloud editing service. However, the SKILL.md describes automatically obtaining an anonymous token when NEMO_TOKEN is not present, making the 'required' designation inconsistent with runtime behavior. Also the frontmatter's configPaths (if used) may cause the skill to look at ~/.config/nemovideo/ — this is plausible but not explained in registry metadata.

Persistence & Privilege

The skill does not request always:true and does not attempt to modify system-wide settings. It stores a session_id for active operations (normal behavior) but does not require permanent system presence or elevated privileges.

Assessment

This skill uploads your raw videos to a third‑party cloud backend (mega-api-prod.nemovideo.ai) for processing. If you care about privacy or copyright, verify that service's policies before uploading media. The skill prefers a NEMO_TOKEN (declared primary) but can request an anonymous token itself — understand whether you want to supply your own token (to use a paid/registered account) or rely on anonymous credentials with limited credits/expiry. Note the small metadata inconsistency (config path listed in the SKILL.md frontmatter but not in registry metadata) — harmless but worth being aware of. There are no code files or installers to audit here, but that also means the static scanner had nothing to check; the backend calls are the main risk surface. If you decide to proceed, consider using a dedicated service account/token with limited scope or test with non-sensitive footage first.

Getting Started

Share your raw video footage and I'll get started on AI video editing. Or just tell me what you're thinking.

Try saying:

• "edit my raw video footage"
• "export 1080p MP4"
• "cut dead air, add transitions, and"

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.

YouTube Video Editor Remastered — Edit and Export YouTube Videos

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

Say you have a 10-minute unedited YouTube vlog recording and want to cut dead air, add transitions, and sync background music to the timeline — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: splitting your video into shorter segments before uploading speeds up processing significantly.

Matching Input to Actions

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

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 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

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.

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

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 → "cut dead air, add transitions, and sync background music to the timeline" → 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 "cut dead air, add transitions, and sync background music to the timeline" — 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 widest YouTube compatibility and smaller file size.