Video Editing And Ai

Skip the learning curve of professional editing software. Describe what you want — cut the pauses, add transitions, and export a clean final video — and get...

Security Scan

The skill's requested credential and runtime actions align with a cloud-based video-editing service; it will upload your videos to a remote API and obtain/use a NEMO_TOKEN, which is coherent with its stated purpose but has some minor metadata inconsistencies and privacy implications you should understand before installing.

Purpose & Capability

Name/description (AI video editing) matches what the instructions do: create sessions, upload video files, run remote renders, and return a download URL. The primary environment variable (NEMO_TOKEN) is appropriate for authenticating to the described cloud API.

Instruction Scope

Instructions are narrowly focused on session creation, SSE-based editing messages, uploads, and export polling. They require reading NEMO_TOKEN (or obtaining an anonymous token from the service) and may check the agent's install path to set an attribution header. Important privacy note: user-supplied videos and potentially generated metadata are uploaded to an external endpoint (mega-api-prod.nemovideo.ai). The skill explicitly tells the agent to not expose tokens, but it will transmit user content and metadata to a third party as part of normal operation.

Install Mechanism

Instruction-only skill with no install spec and no code files — nothing is written to disk by an installer. This is the lowest-risk install model.

Credentials

The skill only requests a single credential (NEMO_TOKEN), which is proportionate for a remote editing API. Minor inconsistency: registry metadata reported no required config paths, but the skill frontmatter references a config path (~/.config/nemovideo/) and runtime instructions read install paths to set X-Skill-Platform. This requires filesystem access beyond just reading an env var and should be noted.

Persistence & Privilege

Skill is not force-included (always: false) and does not request elevated or persistent privileges. It does not instruct modification of other skills or system-wide settings. Autonomous invocation is allowed (default) but not by itself a problem.

Assessment

This skill appears to do what it says — it uploads raw videos and uses a cloud service to edit and render results. Before installing: (1) Confirm you trust the service domain (mega-api-prod.nemovideo.ai) because your videos and metadata will be sent there; (2) Understand that NEMO_TOKEN grants access to that account/session—if you provide a long-lived token, treat it like a password and rotate or revoke it if needed; (3) Be aware the skill may create an anonymous token automatically if none is present (the agent will POST to the API), and it may check local paths to set attribution headers; (4) Avoid sending sensitive or private videos unless you’ve verified the provider’s privacy policy and security posture. If any of the above is unacceptable, do not install or do not provide a NEMO_TOKEN.

Getting Started

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

Try saying:

• "edit a 3-minute unedited screen recording into a 1080p MP4"
• "cut the pauses, add transitions, and export a clean final video"
• "automatically editing raw footage into polished videos using AI for content creators and marketers"

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 Editing and AI — Edit and Export AI Videos

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

A quick example: upload a 3-minute unedited screen recording, type "cut the pauses, add transitions, and export a clean final video", 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 give more accurate AI cuts.

Matching Input to Actions

User prompts referencing video editing and 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.

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.

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

• X-Skill-Source: video-editing-and-ai
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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.

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

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

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.

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 pauses, add transitions, and export a clean final video" → 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 the pauses, add transitions, and export a clean final video" — 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 balance of quality and file size.