Video Editor Ai Generator

Skip the learning curve of professional editing software. Describe what you want — cut the silent pauses, add background music, and generate subtitles — and...

Security Scan

The skill appears to do what it says (cloud video editing via the NemoVideo API) and requests only a single service token, but there are a few mismatches and minor scope details you should review before installing.

Purpose & Capability

The skill's name/description align with its runtime instructions: it calls a NemoVideo cloud API and needs a NEMO_TOKEN. However, the frontmatter metadata in SKILL.md lists a config path (~/.config/nemovideo/) even though the registry metadata reported no required config paths — this discrepancy should be clarified. Also the runtime asks the agent to detect an install path (~/.clawhub/, ~/.cursor/skills/) which requires reading certain filesystem locations; that is plausible for attribution but worth noting.

Instruction Scope

Instructions limit network activity to the nemovideo.ai endpoints and describe uploading user-provided files and streaming SSE. They instruct generating an anonymous token (POST to /api/auth/anonymous-token) and saving session_id. The skill tells the agent to read its own YAML frontmatter and detect install paths, and references a config path in metadata; reading those file locations is beyond pure API calls and could access user configs if present. The instructions explicitly say not to print tokens or raw JSON, which is good.

Install Mechanism

This is an instruction-only skill with no install spec or code files, so nothing is written to disk by an installer. That is the lowest-risk install model.

Credentials

The skill requests exactly one credential (NEMO_TOKEN), which is appropriate for a cloud API client. The frontmatter also lists a config path (~/.config/nemovideo/) which could contain additional secrets or settings; the registry metadata earlier did not list required config paths — this inconsistency should be resolved. The skill also offers an anonymous-token flow, which is a safer alternative to using a long-lived token.

Persistence & Privilege

always:false and normal autonomous invocation are set. The skill does not request global modifications or permanent system-wide privileges. The only persistence implied is storing session_id and using NEMO_TOKEN for API calls, which is standard for an API client.

Assessment

This skill appears coherent for cloud-based AI video editing, but check these before installing: (1) Understand that any uploaded video will be sent to mega-api-prod.nemovideo.ai — do not upload sensitive or private footage unless you trust their privacy/retention policy. (2) Prefer the anonymous-token flow for temporary access rather than setting a long-lived NEMO_TOKEN in your environment. (3) Clarify the metadata mismatch: SKILL.md lists ~/.config/nemovideo/ but the registry said no config paths; confirm what the skill will read from disk. (4) The skill detects install paths (~/.clawhub, ~/.cursor/skills) to set an attribution header — this requires filesystem access only to those paths; verify you’re comfortable with that. (5) Don’t set NEMO_TOKEN to unrelated high-privilege credentials (e.g., cloud provider keys). If you need higher assurance, ask the publisher for a privacy policy, data retention details, and to confirm exactly which local paths the skill will read.

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 the silent pauses, add background"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Video Editor AI Generator — Generate and Edit Videos with AI

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 2-minute unedited screen recording and want to cut the silent pauses, add background music, and generate subtitles — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 60 seconds process significantly faster and use fewer credits.

Matching Input to Actions

User prompts referencing video editor ai 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.

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

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

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

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.

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 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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut the silent pauses, add background music, and generate subtitles" — 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 widest compatibility across platforms.

Common Workflows

Quick edit: Upload → "cut the silent pauses, add background music, and generate subtitles" → 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.