Video Editing With Macbook

edit video clips into polished edited clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. Mac users and content creators use it for edit...

Security Scan

The skill's requests and runtime instructions are coherent with a cloud video‑editing service: it only needs a single service token and describes using that API to upload, edit, and export videos — nothing in the skill suggests unrelated access or surprising install actions.

Purpose & Capability

Name/description (cloud AI video editing) matches what the SKILL.md instructs: exchanging a single service token (NEMO_TOKEN), creating sessions, uploading clips, running SSE for edits, and exporting rendered MP4s. Requiring a service token is proportionate to the stated purpose.

Instruction Scope

Instructions are focused on interacting with the nemovideo.ai API (session creation, upload, SSE, render polling). The SKILL.md says to read the file's YAML frontmatter for attribution and to 'detect' install path for a header — this is limited scope (self-attribution) but worth noting since it implies the agent may read its own skill file or determine an install path.

Install Mechanism

Instruction-only skill with no install spec and no downloads. No binaries or archives are requested, which is the lowest-risk install profile.

Credentials

The skill declares a single primary credential (NEMO_TOKEN) which is appropriate for a hosted editing API. Minor inconsistency: the SKILL.md frontmatter also lists a config path (~/.config/nemovideo/) for attribution metadata, while the registry metadata reported no required config paths. The instructions themselves do not require any additional unrelated secrets or credentials.

Persistence & Privilege

Skill is not always-included and does not ask to modify other skills or system-wide settings. It operates per-session against the API and does not request elevated or persistent platform privileges.

Assessment

This skill appears to do what it says: it uploads your video files to a third-party API (mega-api-prod.nemovideo.ai) for cloud GPU editing and returns a downloadable MP4. Before installing/using it, consider: 1) Privacy — you will be uploading the raw video to an external service; avoid sending sensitive footage unless you trust the provider and have read their terms/privacy policy. 2) Secrets — if you set NEMO_TOKEN in your environment, keep it secret; the skill also supports generating a short-lived anonymous token if you prefer not to provide your own. 3) Verify endpoints — the skill points at mega-api-prod.nemovideo.ai; confirm that domain and service are legitimate if you rely on compliance guarantees. 4) Note the small metadata mismatch about a config path in the SKILL.md frontmatter versus registry metadata — likely benign (self-attribution) but worth awareness. If any of these points worry you, avoid providing private videos or a long-lived token and prefer the anonymous token flow.

Getting Started

Send me your video clips and I'll handle the AI video editing. Or just describe what you're after.

Try saying:

• "edit a 3-minute MacBook screen recording or camera footage into a 1080p MP4"
• "trim the long pauses, add transitions, and export a clean final cut"
• "editing raw MacBook footage into a clean final video without desktop software for Mac users and content creators"

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 Editing with MacBook — Edit and Export Polished Videos

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

Here's a typical use: you send a a 3-minute MacBook screen recording or camera footage, ask for trim the long pauses, add transitions, and export a clean final cut, 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 — MOV files from macOS screen recordings upload and process without any conversion needed.

Matching Input to Actions

User prompts referencing video editing with macbook, 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: video-editing-with-macbook
• 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

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

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 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)

Common Workflows

Quick edit: Upload → "trim the long pauses, add transitions, and export a clean final cut" → 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 "trim the long pauses, add transitions, and export a clean final cut" — 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.