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Trimmer By Link
作者
whitejohnk-26
· GitHub ↗
· v1.0.0
· MIT-0
68
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install trimmer-by-link
功能描述
trim video URL link into trimmed video clips with this skill. Works with YouTube, Vimeo, MP4, MOV files up to 500MB. content creators, researchers, social me...
安全使用建议
This skill appears to be a client for a remote video-trimming service (nemovideo.ai) and requires a service token (NEMO_TOKEN) or will obtain a short-lived anonymous token. Before installing: (1) Confirm you trust mega-api-prod.nemovideo.ai (privacy of uploaded URLs/videos, retention, who can access generated clips). (2) Verify the mismatch: SKILL.md frontmatter lists ~/.config/nemovideo/ while registry metadata lists no config paths — ask the author whether the skill will read local config files. (3) Be aware the skill may inspect agent install paths (~/.clawhub, ~/.cursor/skills) for attribution headers; if you prefer not to expose local paths, ask for an option to disable that behavior. (4) Because the skill sends video URLs and possibly uploaded media to a third-party service, avoid sending private or sensitive videos unless you trust the service/legal terms. If the author can provide a homepage, privacy policy, or source repo, review those to raise confidence.
功能分析
Type: OpenClaw Skill
Name: trimmer-by-link
Version: 1.0.0
The skill is a legitimate interface for a cloud-based video editing service (nemovideo.ai). It provides instructions for the agent to manage authentication via environment variables or anonymous token generation and outlines the API workflow for uploading, trimming, and exporting video clips. All identified behaviors, including network requests to mega-api-prod.nemovideo.ai and access to service-specific configuration paths (~/.config/nemovideo/), are strictly aligned with the stated purpose of the tool and do not show evidence of malicious intent or data exfiltration.
能力评估
Purpose & Capability
Name/description (trim video links) align with the only required credential (NEMO_TOKEN) and the documented API endpoints on mega-api-prod.nemovideo.ai. However, the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata lists no required config paths — this mismatch is unexplained and worth verifying. Requiring a NEMO_TOKEN is proportionate to a remote render service.
Instruction Scope
SKILL.md gives explicit instructions to use NEMO_TOKEN or obtain an anonymous token via network calls to mega-api-prod.nemovideo.ai, create sessions, upload URLs/files, read SSE, and poll status — all expected for a remote trimming service. It also instructs the agent to read the skill's YAML frontmatter for attribution and to detect install path (~/.clawhub/, ~/.cursor/skills/) to set X-Skill-Platform; that requires accessing local paths and is not strictly necessary for trimming functionality (it’s attribution-related). No instructions ask for unrelated system secrets, but the filesystem checks and attribution requirements are scope-expanding and should be validated.
Install Mechanism
Instruction-only skill with no install spec and no code files. This is lower risk because nothing is written or executed locally by an installer. All heavy work is performed on the remote service.
Credentials
Only NEMO_TOKEN is required (declared as primaryEnv) which is consistent with a service API key. The SKILL.md also documents an anonymous-token flow (POST to the API to get a short-lived token) which is reasonable. The frontmatter's mention of a local config path (~/.config/nemovideo/) is not explained by registry metadata and could imply optional local credential/config usage; flag that mismatch and confirm whether any local files will be read.
Persistence & Privilege
always:false and no install hooks — the skill does not request permanent system presence or elevated privileges. Autonomous invocation is allowed by default; that is normal. The skill does instruct the agent to read local install paths/frontmatter for attribution, but it doesn't request modifying other skills or writing system-wide settings.
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-by-link - 安装完成后，直接呼叫该 Skill 的名称或使用
/trimmer-by-link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 Trimmer by Link — trim video links into clips.
- Supports trimming YouTube, Vimeo, MP4, and MOV links up to 500MB, with export as 1080p MP4.
- Offers fast, cloud-based video processing — typically delivers results in 20-40 seconds.
- Allows processing of video URLs directly without requiring downloads.
- Features session-based workflow with automatic free trial token generation if needed.
- Built-in handling for authentication, credits, common errors, and backend API endpoints.
- Action routing based on user intent for exporting, checking credits, status, upload, and editing.
元数据
常见问题
Trimmer By Link 是什么？
trim video URL link into trimmed video clips with this skill. Works with YouTube, Vimeo, MP4, MOV files up to 500MB. content creators, researchers, social me... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 68 次。
如何安装 Trimmer By Link？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install trimmer-by-link」即可一键安装，无需额外配置。
Trimmer By Link 是免费的吗？
是的，Trimmer By Link 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Trimmer By Link 支持哪些平台？
Trimmer By Link 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 By Link？
由 whitejohnk-26（@whitejohnk-26）开发并维护，当前版本 v1.0.0。
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