Ai Editor Generator

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

Security Scan

The skill's requirements and runtime instructions are coherent with a remote AI video-editing service: it asks for a single service token, uploads user video files, and calls the described external API endpoints — nothing in the package suggests it is trying to do unrelated or hidden actions.

Purpose & Capability

The skill claims to perform remote GPU-based video editing and its instructions require a NEMO_TOKEN and describe API endpoints for session creation, upload, render, credits, and state. These environment and network requirements are appropriate for the stated purpose. Minor inconsistency: the registry metadata reported no required config paths, but the SKILL.md frontmatter metadata lists a config path (~/.config/nemovideo/). That mismatch should be reconciled but does not by itself indicate malicious intent.

Instruction Scope

The SKILL.md stays largely within the expected scope (create session, upload footage, send SSE messages, poll render). It also instructs the agent to generate a UUID and call an anonymous-token endpoint if NEMO_TOKEN is absent — a reasonable fallback but means the agent will make network calls to obtain a token. The instructions also ask the agent to read the skill's own YAML frontmatter and to detect install paths (e.g., ~/.clawhub/ or ~/.cursor/skills/) to set X-Skill-Platform; reading install path metadata is minor scope creep and could reveal local path structure. Aside from that, there are no instructions to read unrelated system files or unrelated environment variables.

Install Mechanism

No install spec or code files are present; this is instruction-only. That minimizes on-disk persistence and supply-chain risk.

Credentials

Only a single credential (NEMO_TOKEN) is declared as required, which is proportional for a remote API service. The skill also documents an anonymous-token flow that generates a temporary token server-side if no token is provided. No unrelated secrets or multiple external credentials are requested.

Persistence & Privilege

The skill does not request always:true and has no install-time hooks. It does mention that session tokens may leave orphaned cloud jobs if a client disconnects, but it does not request elevated system privileges or persistent installation.

Assessment

This skill appears to be what it says: a client for a remote video-editing API. Before installing or using it, consider: (1) it will upload whatever footage you hand it to a third-party endpoint (https://mega-api-prod.nemovideo.ai) — do not upload sensitive videos unless you trust the service and its privacy policy; (2) if you don't supply NEMO_TOKEN the skill will obtain an anonymous token by POSTing a generated client UUID to the API — this is expected but does make an outbound network call; (3) the skill may inspect local install paths to set an attribution header — while minor, this touches filesystem metadata; (4) reconcile the small metadata mismatch (registry metadata vs SKILL.md frontmatter) with the publisher if you need provenance; (5) if you decide to proceed, test with non-sensitive sample footage and monitor network activity and token usage, and prefer using a disposable token or account if available.

Getting Started

Share your raw video footage and I'll get started on AI 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"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

• Generate a UUID as client identifier
• POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
• The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

AI Editor Generator — Generate and Export Edited Videos

Send me your raw video footage 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 2-minute unedited screen recording, type "cut out silences, 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 3 minutes process significantly faster.

Matching Input to Actions

User prompts referencing ai editor generator, 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.

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

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

• X-Skill-Source: ai-editor-generator
• 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

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 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.

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.