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Video Trimmer Js
作者
vcarolxhberger
· GitHub ↗
· v1.0.0
· MIT-0
70
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install video-trimmer-js
功能描述
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...
安全使用建议
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.
功能分析
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).
能力评估
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.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install video-trimmer-js - 安装完成后，直接呼叫该 Skill 的名称或使用
/video-trimmer-js触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
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.
元数据
常见问题
Video Trimmer Js 是什么？
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... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 70 次。
如何安装 Video Trimmer Js？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install video-trimmer-js」即可一键安装，无需额外配置。
Video Trimmer Js 是免费的吗？
是的，Video Trimmer Js 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Video Trimmer Js 支持哪些平台？
Video Trimmer Js 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Video Trimmer Js？
由 vcarolxhberger（@vcarolxhberger）开发并维护，当前版本 v1.0.0。
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