Editor Ai Mac

v1.0.0

Skip the learning curve of professional editing software. Describe what you want — cut the filler pauses, add transitions, and export as MP4 — and get edited...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for mory128/editor-ai-mac.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Editor Ai Mac" (mory128/editor-ai-mac) from ClawHub.
Skill page: https://clawhub.ai/mory128/editor-ai-mac
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: NEMO_TOKEN
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install editor-ai-mac

ClawHub CLI

Package manager switcher

npx clawhub@latest install editor-ai-mac
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high confidence
Purpose & Capability
Name/description (AI video editing) align with the endpoints, upload/export flows, and the single required credential (NEMO_TOKEN). The API host and endpoints in SKILL.md are consistent with a remote render/edit service.
Instruction Scope
Instructions are explicit and limited to: use NEMO_TOKEN (or obtain an anonymous token), create a session, upload files, stream edits via SSE, and call render endpoints. The skill also asks agents to read the skill's YAML frontmatter and detect install path (~/.clawhub, ~/.cursor/skills/) to set X-Skill-Platform — this requires reading local install metadata but is plausible for producing the required attribution headers.
Install Mechanism
Instruction-only skill with no install spec and no downloads or added binaries. Lowest-risk install footprint.
Credentials
Only one environment variable is required (NEMO_TOKEN), which is the expected API bearer token for a remote editing service; the fallback anonymous-token flow is provided as a reasonable convenience.
Persistence & Privilege
Skill is not always-enabled, has no install-time persistence or system-wide config changes, and does not request elevated privileges or credentials belonging to other services.
Assessment
This skill appears coherent for remote AI video editing. Before installing, consider: (1) NEMO_TOKEN is an API bearer token—treat it like a password and only supply a token from a trusted source; (2) uploaded videos (up to 500MB) are sent to the service's domain (mega-api-prod.nemovideo.ai)—review the provider's privacy/retention and terms before uploading sensitive content; (3) the skill may read its own SKILL.md frontmatter and check common install paths to set attribution headers—if you prefer not to allow filesystem checks, confirm how your agent runtime enforces file access controls. If any of these are unacceptable, do not enable the skill or provide a token.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🖥️ Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk976e4m1kw6bg75ttddr5e3kmx852fh6
70downloads
0stars
1versions
Updated 1w ago
v1.0.0
MIT-0

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"
  • "cut the filler pauses, add transitions,"

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.

Editor AI Mac — AI Edit and Export Videos

Send me your video clips 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 screen recording from a MacBook, type "cut the filler pauses, add transitions, and export as MP4", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: MOV files from Mac record natively and upload without conversion.

Matching Input to Actions

User prompts referencing editor ai mac, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip 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

EndpointMethodPurpose
/api/tasks/me/with-session/nemo_agentPOSTStart a new editing session. Body: {"task_name":"project","language":"<lang>"}. Returns session_id.
/run_ssePOSTSend 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>POSTUpload a file (multipart) or URL.
/api/credits/balance/simpleGETCheck remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latestGETFetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambdaPOSTStart 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.

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

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

All requests must include: Authorization: Bearer <NEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 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

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.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend saysYou 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

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 → "cut the filler 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 "cut the filler 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 platforms and devices.

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