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Video Trimmer Js
by
vcarolxhberger
· GitHub ↗
· v1.0.0
· MIT-0
70
Downloads
0
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0
Active Installs
1
Versions
Install in OpenClaw
/install video-trimmer-js
Description
Turn a 10-minute raw screen recording into 1080p trimmed video clips just by typing what you need. Whether it's cutting unwanted segments from video files in...
Usage Guidance
This skill appears to be what it says (a remote video-trimming frontend) but contains a few red flags you should consider before installing: 1) Metadata mismatch — the SKILL.md references a config directory (~/.config/nemovideo/) while registry metadata reported no config paths; ask the publisher to clarify where the skill will read/write files. 2) Token creation/persistence — the skill will auto-request an anonymous token and wants to 'store' it for later use; confirm where that token is saved and whether you prefer to supply your own NEMO_TOKEN instead of letting the skill generate one. 3) File uploads — the skill uploads your video files to mega-api-prod.nemovideo.ai; do not upload sensitive content unless you trust that remote service and its privacy/retention policies. 4) Headers/install-path probing — the skill attempts to derive an X-Skill-Platform header by inspecting install path patterns; if you are concerned about filesystem probing, request that the skill not probe or that you provide the platform value explicitly. If you decide to proceed, prefer manually provisioning NEMO_TOKEN, verify the service domain and privacy policy, and restrict uploads to non-sensitive material.
Capability Analysis
Type: OpenClaw Skill
Name: video-trimmer-js
Version: 1.0.0
The skill automates network interactions with a remote backend (mega-api-prod.nemovideo.ai), including automated token acquisition and session management. It instructs the agent to fingerprint the user's environment by detecting installation paths (e.g., ~/.cursor/skills/) and requests access to local configuration directories (~/.config/nemovideo/). While these capabilities are plausibly required for the stated cloud-based video trimming service, the automated network activity and environment detection represent high-risk behaviors in an agentic context (SKILL.md).
Capability Assessment
Purpose & Capability
The skill claims to perform cloud GPU video trimming and requires a single API credential (NEMO_TOKEN) — that is coherent. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata stated no required config paths, an inconsistency that should be resolved.
Instruction Scope
Runtime instructions direct the agent to obtain an anonymous token if NEMO_TOKEN is missing, create a session_id, upload user video files, stream SSE, poll render status, and include custom headers derived from the agent's install path. Those are expected for a remote render service, but the instructions also imply reading/writing persistent state (saving token/session_id) and probing install paths—actions outside pure 'call API' scope and not fully specified where or how to store secrets.
Install Mechanism
No install spec and no code files — the skill is instruction-only, so nothing is written to disk by an installer. That lowers supply-chain risk.
Credentials
Only one credential (NEMO_TOKEN) is requested, which is proportionate to calling the Nemovideo API. However, the skill instructs automatic creation of a 7-day anonymous token and to 'store' it; it's unclear where this token is persisted (env var, config file under ~/.config/nemovideo/, or agent storage), which affects confidentiality and lifetime of the secret.
Persistence & Privilege
The skill does not set always:true, but it instructs persisting tokens/session IDs and deriving X-Skill-Platform by inspecting install paths (e.g., ~/.clawhub/, ~/.cursor/skills/). That implies filesystem probing and token persistence that were not declared in registry metadata. Automatic creation and storage of credentials increases risk if you don't control where the secret is saved.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install video-trimmer-js - After installation, invoke the skill by name or use
/video-trimmer-js - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of Video Trimmer JS — trim and export video clips effortlessly in your browser.
- Upload screen recordings or video files and describe trimming/editing tasks in plain language.
- Automatic backend connection, with simple token-based authentication for free usage credits.
- Fast cloud rendering with GPU acceleration; returns 1080p exports in as little as 20-40 seconds.
- Handles a variety of formats (mp4, mov, avi, webm, etc.) up to 500MB per file.
- Natural language commands recognized for trimming, aspect ratio, overlays, audio tracks, and more.
- Error handling covers token, session, file, and credit issues, guiding users as needed.
Metadata
Frequently Asked Questions
What is Video Trimmer Js?
Turn a 10-minute raw screen recording into 1080p trimmed video clips just by typing what you need. Whether it's cutting unwanted segments from video files in... It is an AI Agent Skill for Claude Code / OpenClaw, with 70 downloads so far.
How do I install Video Trimmer Js?
Run "/install video-trimmer-js" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Video Trimmer Js free?
Yes, Video Trimmer Js is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Video Trimmer Js support?
Video Trimmer Js is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Video Trimmer Js?
It is built and maintained by vcarolxhberger (@vcarolxhberger); the current version is v1.0.0.
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