Free Video Editor Mac

Turn a 3-minute screen recording from a MacBook into 1080p edited MP4 clips just by typing what you need. Whether it's editing and trimming video clips on a...

Security Scan

The skill's requests and runtime instructions are coherent with a cloud-based video editing service: it uses a single service token, uploads user media to a remote API, and does not request unrelated credentials or install arbitrary code, but the publisher is unknown so exercise caution before uploading sensitive content.

Purpose & Capability

The name/description (cloud AI video editing) aligns with the required NEMO_TOKEN and the API endpoints documented in SKILL.md. Declared config path (~/.config/nemovideo/) and primaryEnv NEMO_TOKEN are consistent with a client for the nemovideo backend. There are no unrelated binaries or extraneous credentials requested.

Instruction Scope

Instructions are focused on connecting to the nemovideo API, uploading user media, creating sessions, streaming SSE, and polling render status — all appropriate for a cloud editor. The skill will (a) upload user files to a third-party service and (b) generate and store anonymous tokens if NEMO_TOKEN is missing; both are expected but material to privacy. The doc also references detecting an install path to set an attribution header, which implies reading agent install paths or environment to decide X-Skill-Platform — this is minor but out-of-band relative to pure editing logic.

Install Mechanism

There is no install spec and no code files; this is instruction-only, so nothing will be written to disk by the skill itself during installation. This is the lowest-risk install posture.

Credentials

Only a single service credential (NEMO_TOKEN) and an optional config path are required — proportional to the described functionality. However, the token grants access to the user's session and uploads on the third-party service, so it is sensitive: generating/storing anonymous tokens automatically is convenient but means the skill can operate without a user-provided credential and will create credentials tied to the agent. The SKILL.md does not request unrelated secrets.

Persistence & Privilege

The skill does not request always:true, does not modify other skills, and is user-invocable only. Autonomous invocation is allowed (platform default) but not combined with elevated privileges in this skill.

Assessment

This skill appears to do exactly what it says: it uploads videos to nemovideo.ai and runs cloud renders using a NEMO_TOKEN. Before installing or using it, consider: (1) the service will receive any video you upload — avoid sending confidential or private recordings; (2) the skill can auto-create and store an anonymous token if NEMO_TOKEN is not set, which means it will operate without you manually providing credentials; (3) there is no publisher or homepage listed — verify the service reputation and privacy policy if you plan to process sensitive content; and (4) if you need stronger control, only use the skill when you can supply and later revoke a dedicated token, and inspect any local files/config the agent may read (the skill may detect install paths for attribution headers).

Getting Started

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

Try saying:

• "edit my video clips"
• "export 1080p MP4"
• "trim 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.

Free Video Editor for Mac — Edit and Export Videos Online

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 screen recording from a MacBook, ask for trim the pauses, add transitions, and export as MP4, 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.

Matching Input to Actions

User prompts referencing free video editor mac, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint	Method	Purpose
/api/tasks/me/with-session/nemo_agent	POST	Start a new editing session. Body: {"task_name":"project","language":"<lang>"}. Returns session_id.
/run_sse	POST	Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/<sid>	POST	Upload a file (multipart) or URL.
/api/credits/balance/simple	GET	Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latest	GET	Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda	POST	Start export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is free-video-editor-mac, 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).

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

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

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.

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)

Common Workflows

Quick edit: Upload → "trim the pauses, add transitions, and export as MP4" → 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 pauses, add transitions, and export as MP4" — 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 Mac and web platforms.