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Trimmer Linux
作者
susan4731-wilfordf
· GitHub ↗
· v1.0.0
· MIT-0
45
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install trimmer-linux
功能描述
Turn a 10-minute screen recording from a Linux session into 1080p trimmed video clips just by typing what you need. Whether it's trimming and cutting video f...
安全使用建议
This skill generally behaves like a normal cloud-based video editor: it uploads files to mega-api-prod.nemovideo.ai and uses a NEMO_TOKEN (or an anonymous token it can generate) to authenticate. Before installing: (1) Confirm you trust the nemovideo.ai domain and review its privacy/retention policy for uploaded videos; (2) avoid supplying a privileged/production token — use an anonymous or limited token for testing; (3) be aware the skill's instructions ask the agent to detect install paths on your system (e.g., ~/.clawhub/, ~/.cursor/skills/) and to read the SKILL.md frontmatter — this filesystem probing is unnecessary for trimming and may leak information about your environment; (4) the SKILL.md lists a config path (~/.config/nemovideo/) even though registry metadata did not — ask the publisher why and whether the skill will access that directory; (5) test first with non-sensitive, short sample videos to confirm exactly what is uploaded and returned. If you are uncomfortable with filesystem probing or uploading sensitive recordings, do not enable the skill until the developer clarifies these points.
功能分析
Type: OpenClaw Skill
Name: trimmer-linux
Version: 1.0.0
The skill bundle provides instructions for an AI agent to interface with a cloud-based video editing service (nemovideo.ai). It outlines standard procedures for authentication, session management, file uploads, and polling for render status. The network activity and data handling are consistent with the stated purpose of trimming videos on remote GPUs, and no indicators of malicious intent or unauthorized data access were found.
能力评估
Purpose & Capability
The skill claims to perform cloud-based video trimming and its network endpoints, auth flow, and file upload instructions align with that purpose. Requesting a NEMO_TOKEN (or creating an anonymous token) is proportionate for a cloud service. However, the frontmatter embedded in SKILL.md also lists configPaths ("~/.config/nemovideo/") even though the registry metadata earlier reported no required config paths — this mismatch suggests sloppy packaging or undocumented filesystem access.
Instruction Scope
The runtime instructions explicitly tell the agent to: generate tokens, POST uploads and SSE messages to an external API (expected), and also to read this file's YAML frontmatter and detect install path strings (e.g., checking ~/.clawhub/ or ~/.cursor/skills/) to set an X-Skill-Platform header. Detecting install path implies probing user filesystem locations, which is not necessary to trim videos and expands the skill's scope into user-host environment inspection. The instructions also require storing session_id and using attribution headers on every API call; both are operationally plausible but the install-path detection is unnecessary and privacy-sensitive.
Install Mechanism
There is no install spec and no code files — the skill is instruction-only. That minimizes supply-chain risk because nothing is downloaded or written by an installer. Network calls to the service are the main runtime surface.
Credentials
The only declared required env var is NEMO_TOKEN (primary credential), which is appropriate for a cloud video service. The instructions further provide an anonymous-token fallback (requests a UUID and exchanges it at the service) so a pre-set NEMO_TOKEN is optional. That is sensible, but you should treat any token (anonymous or not) as allowing uploads of your videos to a third-party; confirm the token's scope, retention, and privacy rules before use. Also note the SKILL.md metadata lists a config path that was not declared in the registry metadata — another inconsistency.
Persistence & Privilege
The skill does not request 'always: true' and is user-invocable only. It instructs the agent to create and save a session_id for a short-lived editing session (expected). There is no request to modify other skills or global agent settings. The main privilege is network access to upload potentially sensitive video files to the external API.
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 trimmer-linux - 安装完成后，直接呼叫该 Skill 的名称或使用
/trimmer-linux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 — Trim and export Linux video clips using cloud GPU processing, with natural language commands.
- Upload video/audio/image files, then describe trims/cuts you want; export 1080p MP4s in ~20–40 sec per clip.
- Handles session management and free token setup automatically; supports anonymous usage (100 credits, 7 days).
- Natural-language input mapped to actions like export, check credits, show timeline state, and more.
- Robust cloud render pipeline: jobs run on GPU, with error handling for session, token, credit, and file issues.
- No installation required on Linux systems; works in-browser with a simple, user-guided workflow.
元数据
常见问题
Trimmer Linux 是什么？
Turn a 10-minute screen recording from a Linux session into 1080p trimmed video clips just by typing what you need. Whether it's trimming and cutting video f... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 45 次。
如何安装 Trimmer Linux？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install trimmer-linux」即可一键安装，无需额外配置。
Trimmer Linux 是免费的吗？
是的，Trimmer Linux 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Trimmer Linux 支持哪些平台？
Trimmer Linux 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 Trimmer Linux？
由 susan4731-wilfordf（@susan4731-wilfordf）开发并维护，当前版本 v1.0.0。
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