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vcarolxhberger

Editor Clips

by vcarolxhberger · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install editor-clips
Description
Skip the learning curve of professional editing software. Describe what you want — trim the pauses, cut the best 30 seconds, and add a fade transition — and...
README (SKILL.md)

Getting Started

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

Try saying:

  • "edit my video clips"
  • "export 1080p MP4"
  • "trim the pauses, cut the best"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

  • Generate a UUID as client identifier
  • POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
  • Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Editor Clips — Trim and Export Edited Clips

This tool takes your video clips and runs AI clip editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 2-minute raw interview clip and want to trim the pauses, cut the best 30 seconds, and add a fade transition — the backend processes it in about 30-60 seconds 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 editor clips, 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.

All requests must include: Authorization: Bearer \x3CNEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

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

  • X-Skill-Source: editor-clips
  • 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":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/\x3Csid>/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_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> 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=\x3Cid>, 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

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 pauses, cut the best 30 seconds, and add a fade transition" → Download MP4. Takes 30-60 seconds 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, cut the best 30 seconds, and add a fade transition" — 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.

Usage Guidance
Before installing, understand that this skill sends selected media and editing instructions to NemoVideo's cloud API and uses a NEMO_TOKEN or anonymous token for access. Avoid uploading sensitive videos unless you trust that provider's handling of the data.
Capability Analysis
Type: OpenClaw Skill Name: editor-clips Version: 1.0.0 The 'editor-clips' skill facilitates AI video editing by connecting to an external API (mega-api-prod.nemovideo.ai). It exhibits risky capabilities including network communication, local file access for uploads, and the management of authentication tokens (NEMO_TOKEN). It also includes instructions for the agent to probe its own installation path to determine the host platform. While these behaviors are plausibly aligned with the stated purpose of the skill, the combination of network/file access and environment discovery meets the provided criteria for a suspicious classification in the absence of explicit malicious intent.
Capability Assessment
Purpose & Capability
The skill's stated purpose is cloud-based clip editing and export, and the documented upload, edit, render, and download API workflows align with that purpose.
Instruction Scope
Instructions allow first-use connection setup and backend-driven workflow translation, but the actions described remain scoped to the NemoVideo editing/render API.
Install Mechanism
There is no install spec and no code files; the skill is instruction-only, and the static scanner had no code to analyze.
Credentials
The skill requires or obtains a NEMO_TOKEN for the video-processing backend, which is expected for the service but should be treated as a credential.
Persistence & Privilege
The skill keeps a session_id for operations and may leave cloud render jobs running if abandoned, but no local persistence, background worker, or privilege escalation is described.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install editor-clips
  3. After installation, invoke the skill by name or use /editor-clips
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Editor Clips 1.0.0 — Initial Release - Launches easy AI-powered video editing: upload a clip and describe your edits to get finished clips fast. - Supports MP4, MOV, AVI, WebM uploads up to 500MB and exports in multiple formats. - Includes automatic setup with free trial credits, session management, and cloud rendering. - Offers quick workflows: trim pauses, cut best segments, add effects, and export with simple instructions. - Handles all backend interactions transparently — no need for editing knowledge or manual software setup.
Metadata
Slug editor-clips
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Editor Clips?

Skip the learning curve of professional editing software. Describe what you want — trim the pauses, cut the best 30 seconds, and add a fade transition — and... It is an AI Agent Skill for Claude Code / OpenClaw, with 50 downloads so far.

How do I install Editor Clips?

Run "/install editor-clips" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Editor Clips free?

Yes, Editor Clips is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Editor Clips support?

Editor Clips is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Editor Clips?

It is built and maintained by vcarolxhberger (@vcarolxhberger); the current version is v1.0.0.

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