Tiktok Video Editor For Pc

edit raw video clips into TikTok-ready clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. TikTok creators use it for editing and format...

Security Scan

The skill's declared purpose (cloud-based TikTok video editing) matches most of its runtime instructions, but there are a few inconsistencies and privacy/operational risks you should understand before installing or using it.

Purpose & Capability

Name/description match the instructions: the skill uploads user media to a cloud backend (mega-api-prod.nemovideo.ai), creates sessions, enqueues render jobs, and returns download URLs. However, the registry metadata lists no required config paths while the SKILL.md frontmatter declares a config path (~/.config/nemovideo/). This mismatch is an inconsistency that should be clarified by the publisher.

Instruction Scope

SKILL.md stays within the editing/export domain: it explains token handling, session creation, uploads, SSE handling, polling for status, and export workflow. It instructs the agent to read an env var (NEMO_TOKEN), generate an anonymous token if missing, and include attribution headers. All of these are relevant to a cloud-based editing service. The skill will read the install path to set an X-Skill-Platform header — a limited filesystem check but worth noting.

Install Mechanism

This is instruction-only (no install spec, no code files). No packages or downloads are performed by an installer, which reduces installation risk. Runtime network calls to the third-party backend are the main surface.

Credentials

The only declared required credential is NEMO_TOKEN — appropriate for a remote API. However, SKILL.md's automatic anonymous-token acquisition behavior means the skill will perform network requests to generate and store/use tokens if NEMO_TOKEN is not present. The SKILL.md frontmatter also declares a config path (~/.config/nemovideo/), but the registry metadata indicated no required config paths — this mismatch raises the question whether the skill will read/write that directory and potentially persist tokens there. Because tokens grant access to the backend and uploads include your media, this needs clarification.

Persistence & Privilege

always:false and normal model invocation are used. The skill does not request elevated or always-on privileges. It will, however, create session state on the remote backend and may persist tokens or session IDs locally (implied by the configPath), so check where it stores credentials before use.

What to consider before installing

This skill appears to do what it says (upload videos to a third‑party cloud render service and return edited clips), but it will send any files you provide to mega-api-prod.nemovideo.ai and will either use a NEMO_TOKEN from your environment or request an anonymous token on your behalf. Before installing or using it: 1) Confirm the backend domain and review that service's privacy policy — don't upload sensitive videos (private, legal, medical, financial) unless you're willing to share them with that third party. 2) If you prefer control, set NEMO_TOKEN yourself rather than relying on the skill's anonymous-token flow. 3) Ask the publisher to clarify where tokens and session state are stored (SKILL.md mentions ~/.config/nemovideo/ in the frontmatter but the registry shows no required config paths). 4) Because this is instruction-only and will perform network requests, consider running it in a sandboxed environment if you need stronger isolation. 5) Prefer skills with a visible source/homepage or reputable publisher; this skill has unknown source and no homepage, which reduces accountability.

Getting Started

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

Try saying:

• "edit my raw video clips"
• "export 1080p MP4"
• "cut the video to 30 seconds,"

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.

TikTok Video Editor for PC — Edit and Export TikTok Videos

Send me your raw 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 60-second vertical phone recording, type "cut the video to 30 seconds, add trending text overlays and transitions for TikTok", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: vertical 9:16 video uploads process and export correctly for TikTok without cropping.

Matching Input to Actions

User prompts referencing tiktok video editor for pc, 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: tiktok-video-editor-for-pc
• 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.

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 → "cut the video to 30 seconds, add trending text overlays and transitions for TikTok" → 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 "cut the video to 30 seconds, add trending text overlays and transitions for TikTok" — 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 best TikTok upload compatibility.