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在 OpenClaw 中安装
/install mars-clouds-clustering-custom-distance-metrics
功能描述
Define custom distance/similarity metrics for clustering and ML algorithms. Use when working with DBSCAN, sklearn, or scipy distance functions with applicati...
安全使用建议
This skill is purely documentation and examples for authoring custom distance functions and appears internally consistent. You can safely review and reuse the example code. As a general precaution, avoid executing untrusted metric code in production or with data that must remain private, and consider vectorizing or using compiled implementations for large datasets to avoid performance issues.
功能分析
Type: OpenClaw Skill
Name: mars-clouds-clustering-custom-distance-metrics
Version: 0.1.0
The skill bundle provides standard documentation and code examples for implementing custom distance metrics in Python using sklearn and scipy. The content is purely educational, contains no executable scripts or high-risk commands, and aligns perfectly with its stated purpose of assisting with machine learning clustering tasks in SKILL.md.
能力评估
Purpose & Capability
The name and description (custom distance metrics for clustering/ML) match the SKILL.md examples and guidance. No unrelated binaries, env vars, or capabilities are requested.
Instruction Scope
SKILL.md only contains example Python code and performance notes for defining metrics with sklearn and scipy. It does not instruct reading files, accessing environment variables, contacting external endpoints, or performing actions outside the stated purpose.
Install Mechanism
No install spec or code files are provided; this is instruction-only so nothing will be written to disk or downloaded by the skill.
Credentials
The skill declares no required environment variables, credentials, or config paths — consistent with its purely instructional nature.
Persistence & Privilege
always is false and there are no instructions to modify agent/system configuration or to persist credentials. Autonomous invocation is allowed by default but that is expected and not excessive here.
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 mars-clouds-clustering-custom-distance-metrics - 安装完成后，直接呼叫该 Skill 的名称或使用
/mars-clouds-clustering-custom-distance-metrics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
v0.1.0
Bulk publish from all-task-skills-dedup
元数据
常见问题
custom-distance-metrics 是什么？
Define custom distance/similarity metrics for clustering and ML algorithms. Use when working with DBSCAN, sklearn, or scipy distance functions with applicati... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 82 次。
如何安装 custom-distance-metrics？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install mars-clouds-clustering-custom-distance-metrics」即可一键安装，无需额外配置。
custom-distance-metrics 是免费的吗？
是的，custom-distance-metrics 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
custom-distance-metrics 支持哪些平台？
custom-distance-metrics 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 custom-distance-metrics？
由 lnj22（@lnj22）开发并维护，当前版本 v0.1.0。
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