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Video Trimmer App
作者
peandrover adam
· GitHub ↗
· v1.0.0
· MIT-0
49
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install video-trimmer-app
功能描述
trim video clips into trimmed video clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for cutting unwanted sec...
安全使用建议
This skill appears to implement cloud-based video trimming and needs a single token (NEMO_TOKEN); that is reasonable. Before installing, consider: 1) The skill uploads your video files to https://mega-api-prod.nemovideo.ai — do you trust this third party with potentially sensitive footage? Check their privacy/retention policy. 2) Ask where session tokens and session_id are stored (memory vs written to ~/.config/nemovideo/) and how long they persist; if they are stored on disk, ask how to revoke/delete them. 3) The SKILL.md will auto-create anonymous tokens if none are provided — test with non-sensitive video first. 4) The registry metadata and SKILL.md disagree about config path requirements; request clarification or source/homepage information from the publisher. If you need stronger assurance, ask for the service's privacy docs or for source code/host verification of the backend domain before proceeding.
功能分析
Type: OpenClaw Skill
Name: video-trimmer-app
Version: 1.0.0
The video-trimmer-app skill facilitates video editing by interfacing with a cloud-based API (mega-api-prod.nemovideo.ai). The logic includes standard authentication via anonymous tokens, session management, and file uploads for GPU-accelerated rendering, all of which align with the stated purpose. While it requests access to a specific configuration path (~/.config/nemovideo/) and performs automated network requests for setup, these actions are narrowly scoped to the service's functionality and do not exhibit signs of malicious intent or data exfiltration.
能力评估
Purpose & Capability
The name/description (video trimming, cloud GPU rendering) lines up with the API endpoints and upload/export flow described in SKILL.md and the single required credential (NEMO_TOKEN). However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata said 'Required config paths: none' — this mismatch is unexplained and may indicate the skill expects to read or write local config files.
Instruction Scope
Instructions direct the agent to check/set NEMO_TOKEN, obtain anonymous tokens via an external API, create and store session_id, upload user video files to an external service, and poll rendering endpoints. Uploading user files to a third‑party service is expected for a cloud render skill, but the doc does not specify where session_id or tokens are persisted (memory, agent storage, or the user's filesystem), and it references a local config path. The instructions also require adding attribution headers and explicitly tell the agent not to display raw API responses or token values — this is unusual but not necessarily malicious. Overall the scope includes network I/O and potential local config access; these are coherent with cloud processing but the persistence details are vague.
Install Mechanism
No install spec and no code files (instruction-only) — lowest-risk install model. Nothing is downloaded or written during install by the skill itself, according to the provided package data.
Credentials
Only one environment variable (NEMO_TOKEN) is declared as required and is the primary credential — that is proportionate for a third‑party API integration. The skill will auto-create an anonymous token if NEMO_TOKEN is absent; that behavior is documented but raises questions about where the obtained token/session will be stored. The SKILL.md frontmatter also mentions a config path (~/.config/nemovideo/) which was not listed in registry metadata — this is an unexplained request for filesystem access that could allow persistence of tokens or other data.
Persistence & Privilege
always:false and normal autonomous invocation are fine. Concern arises from unspecified persistence: SKILL.md instructs to 'store the returned session_id for all subsequent requests' but doesn't specify storage location or lifecycle, and frontmatter references a local config directory. This could result in tokens or session IDs being written to disk without clear user-visible controls or cleanup.
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-app - 安装完成后，直接呼叫该 Skill 的名称或使用
/video-trimmer-app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
video-trimmer-app 1.0.0
- Initial release.
- Trim, edit, and export videos (MP4, MOV, AVI, WebM up to 500MB) using a cloud-based processing backend.
- Automatic backend authentication and session management with up to 100 free credits.
- Support for quick trims, batch editing, and iterative workflows—all in 1080p MP4 output.
- Handles files via chat upload; responds to commands for export, credits balance, upload status, and more.
- Robust error handling and detailed guidance for supported formats and workflows.
元数据
常见问题
Video Trimmer App 是什么？
trim video clips into trimmed video clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for cutting unwanted sec... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 49 次。
如何安装 Video Trimmer App？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install video-trimmer-app」即可一键安装，无需额外配置。
Video Trimmer App 是免费的吗？
是的，Video Trimmer App 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Video Trimmer App 支持哪些平台？
Video Trimmer App 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 App？
由 peandrover adam（@peand-rover）开发并维护，当前版本 v1.0.0。
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