Video Editing Ai Best

Turn a 3-minute unedited screen recording into 1080p polished edited clips just by typing what you need. Whether it's automatically editing raw footage into...

Security Scan

The skill's runtime instructions mostly match a cloud video-editing service, but there are metadata inconsistencies and a few behaviors (automatic token minting, detecting install paths, and always sending user video to an external API) that warrant caution before installing.

Purpose & Capability

The declared purpose (cloud video editing) aligns with the runtime behavior (uploading video, creating a session, rendering, returning download URL). However the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) and install-path detection that are not reflected in the registry metadata — this mismatch is unexplained and worth flagging.

Instruction Scope

Instructions direct the agent to read NEMO_TOKEN from env or automatically POST to an external auth endpoint to mint an anonymous token, create sessions, upload files (multipart @/path), and poll for renders. They also instruct the agent to detect install path(s) (e.g. ~/.clawhub/, ~/.cursor/skills/) and to read this file's YAML frontmatter for attribution. Reading those filesystem locations and automatically minting/storing tokens are outside a minimal 'edit a video' description and have privacy implications.

Install Mechanism

This is an instruction-only skill with no install spec and no code files — lowest risk for arbitrary code installation. Nothing is downloaded or written by an installer step.

Credentials

Only one environment variable is declared (NEMO_TOKEN), which fits a cloud API integration. But the SKILL.md will mint and use an anonymous token if NEMO_TOKEN is absent; the frontmatter also lists a config path (not present in registry metadata). The discrepancy between declared configPaths and registry metadata is inconsistent and should be clarified.

Persistence & Privilege

The skill does not request 'always: true' and does not declare system-wide changes. It keeps ephemeral session IDs for operations, which is normal. Autonomous invocation is allowed (platform default) — note that networked skills have wider blast radius when run autonomously.

What to consider before installing

This skill appears to be a wrapper around a cloud video-editing API and will upload your video files to https://mega-api-prod.nemovideo.ai and use a Bearer token (NEMO_TOKEN). Before installing: 1) Verify the skill owner and the API domain (no homepage provided and source is unknown). 2) Consider privacy: any video you upload will go to an external service — avoid sensitive footage. 3) Note the metadata mismatch (registry says no config paths but SKILL.md references ~/.config/nemovideo/ and checks common install locations); ask the author to explain why it needs to inspect filesystem paths. 4) If you don't want the skill to mint an anonymous token or access your env, don't provide NEMO_TOKEN in the agent environment and avoid using the skill. 5) Prefer installing only if you can confirm the backend service is legitimate and you accept that your data is sent to that service.

Getting Started

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

Try saying:

• "edit my raw video footage"
• "export 1080p MP4"
• "cut out silences, 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.

Video Editing AI Best — Edit and Export Polished Videos

Drop your raw video footage in the chat and tell me what you need. I'll handle the AI-powered video editing on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 3-minute unedited screen recording, ask for cut out silences, add transitions, and export a clean final video, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips under 2 minutes process significantly faster and give more precise AI results.

Matching Input to Actions

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

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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.

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)

Error Handling

Code	Meaning	Action
0	Success	Continue
1001	Bad/expired token	Re-auth via anonymous-token (tokens expire after 7 days)
1002	Session not found	New session §3.0
2001	No credits	Anonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001	Unsupported file	Show supported formats
4002	File too large	Suggest compress/trim
400	Missing X-Client-Id	Generate Client-Id and retry (see §1)
402	Free plan export blocked	Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429	Rate limit (1 token/client/7 days)	Retry in 30s once

Common Workflows

Quick edit: Upload → "cut out silences, 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 out silences, 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 for widest compatibility across all platforms and devices.