Video Capcut Ai

edit raw video footage into edited video clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. TikTok creators use it for auto-editing sho...

Security Scan

The skill's behavior mostly matches an auto‑editing cloud service (it uploads videos and uses a NEMO_TOKEN), but there are small inconsistencies and privacy-relevant actions (automatic token minting, reading config/install paths, and sending user files to an external API) that you should understand before installing.

Purpose & Capability

Name/description (cloud AI video editing) align with the runtime instructions (upload, edit, render, download). Requesting a NEMO_TOKEN and calling a rendering API is coherent. However, the SKILL.md frontmatter declares a configPath (~/.config/nemovideo/) while the registry metadata listed no required config paths — this mismatch is unexplained.

Instruction Scope

Instructions stay within the editing workflow (create session, SSE for edits, uploads, export). They also instruct the agent to: check the environment for NEMO_TOKEN, generate an anonymous token via a network call if missing, detect install path to set X-Skill-Platform, and access local file paths for uploads. Those extra steps (auto-token acquisition and probing install/config paths) are reasonable for convenience but broaden what the agent will read and transmit.

Install Mechanism

This is an instruction-only skill with no install spec and no code files — lowest install risk. There is no package download or archive extraction in the manifest.

Credentials

Only NEMO_TOKEN is declared as required, which is proportionate for a cloud API. But the skill’s runtime tells the agent to mint an anonymous token if NEMO_TOKEN is absent and references a config path in frontmatter (~/.config/nemovideo/). That implies potential read access to a local config directory not clearly justified in the top-level registry metadata.

Persistence & Privilege

always:false and the skill does not request permanent platform-wide privileges. It will perform network calls to an external API and may leave jobs running on the vendor's cloud (orphaned jobs if session is closed), which is expected for a cloud render service.

What to consider before installing

This skill will upload your video files and metadata to an external cloud service (mega-api-prod.nemovideo.ai) and requires a NEMO_TOKEN (it will attempt to obtain an anonymous token automatically if you don't supply one). Before installing, consider: 1) privacy — your videos and any embedded metadata will be sent off‑device; 2) verify the service domain and privacy policy if you need confidentiality; 3) the SKILL.md mentions reading a local config path (~/.config/nemovideo/) even though the registry metadata didn't list it — ask the author why the skill needs that and what it will read; 4) avoid supplying unrelated secrets (AWS keys, other tokens); and 5) if you want tighter control, supply a short‑lived token yourself or run uploads through a vetted proxy. If you need me to, I can list the exact API calls the skill will make or produce a minimal checklist of questions to ask the skill author.

Getting Started

Ready when you are. Drop your raw video footage here or describe what you want to make.

Try saying:

• "edit a 60-second vertical phone recording into a 1080p MP4"
• "trim the video, add transitions, and overlay background music"
• "auto-editing short videos for TikTok and Reels for TikTok creators"

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.

Video CapCut AI — AI Edit and Export 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 60-second vertical phone recording and want to trim the video, add transitions, and overlay background music — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: shorter clips under 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing video capcut ai, 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.

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

• X-Skill-Source: video-capcut-ai
• 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.

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.

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.

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 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)

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

Common Workflows

Quick edit: Upload → "trim the video, add transitions, and overlay background music" → 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 "trim the video, add transitions, and overlay background music" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across all platforms.