Ai Video Editor Gpt

Turn a 2-minute unedited screen recording into 1080p edited MP4 videos just by typing what you need. Whether it's editing raw footage into a finished video u...

Security Scan

The skill's declared purpose (cloud AI video editing) matches most of its instructions, but there are inconsistencies and privacy/persistence concerns — notably automatic anonymous token acquisition/storage, a metadata vs. registry mismatch about config paths, and filesystem fingerprinting — you should verify where tokens and uploads go before installing.

Purpose & Capability

The name/description (AI video editing) aligns with requiring a service token (NEMO_TOKEN) and uploading footage to a remote API. However, the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata lists no required config paths, which is an internal inconsistency. The skill also derives X-Skill-Platform by inspecting install paths, which requires reading filesystem locations that are not strictly necessary for core editing functionality.

Instruction Scope

Runtime instructions tell the agent to auto-request an anonymous token (POST to https://mega-api-prod.nemovideo.ai), create and store sessions, and upload user video files (multipart @/path or URL). That means user video content and session tokens will be sent to a third-party API. The SKILL.md also instructs the agent not to display raw API responses or token values and to persist session_id (storage location not specified). These behaviors are within the claimed purpose but broaden the skill's access surface (automatic credential issuance, persistent tokens, filesystem reads for platform detection) and raise privacy/persistence questions.

Install Mechanism

There is no install spec (instruction-only skill), so nothing is written to disk by an installer. This lowers supply-chain risk. Any persistence or file writes would come from runtime behavior described in SKILL.md rather than an installer.

Credentials

Only one environment credential is declared (NEMO_TOKEN), which is appropriate for a cloud-rendering service. The skill also auto-generates an anonymous token if NEMO_TOKEN is absent — reasonable but notable because the token will be created and used without explicit user-provided credentials. The SKILL.md references config paths and install-path detection not declared in the registry, which should be clarified.

Persistence & Privilege

always:false and normal autonomous invocation are used (no elevated platform privilege). However, the skill expects to persist session_id and likely token information for subsequent API calls (frontmatter mentions a config path). Persisting tokens/sessions on disk increases risk if you don't know where/how they're stored or protected.

What to consider before installing

Before installing, confirm these points: (1) The skill uploads your raw videos to https://mega-api-prod.nemovideo.ai — do not use it for sensitive footage unless you trust that domain and its privacy policy. (2) If you don't supply NEMO_TOKEN, the skill will auto-create an anonymous token and use it; ask where tokens and session IDs are stored (the frontmatter suggests ~/.config/nemovideo/). (3) Ask the publisher for a privacy/terms link and for clarification about the config path/metadata mismatch. (4) If you prefer control, supply your own NEMO_TOKEN rather than letting the skill generate one, and avoid installing if you cannot verify the backend/service operator.

Getting Started

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

Try saying:

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

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

AI Video Editor GPT — Edit and Export Finished Videos

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

Here's a typical use: you send a a 2-minute unedited screen recording, ask for cut the pauses, 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 3 minutes process significantly faster and give more precise AI results.

Matching Input to Actions

User prompts referencing ai video editor gpt, 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.

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is ai-video-editor-gpt, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise 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 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

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

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.

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)

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 for widest compatibility across platforms and devices.

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.