Skill Dashboard Visualizer
This skill is designed to enhance the OpenClaw user experience by providing a clear, interactive, and visually appealing dashboard that summarizes the capabilities of all installed skills. It addresses the common pain point of users finding it difficult to remember and utilize the full potential of their diverse skill set.
Core Features
This skill integrates three key functionalities to offer a holistic view and interaction model for managing skills:
- 1. Visual Dashboard (可视化看板):
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Purpose: To present a quick, at-a-glance overview of each installed skill.
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Mechanism: Automatically extracts metadata (name, description) from
SKILL.md files. Each skill is represented as a card with an icon, category tags, and a concise summary of its core abilities. The design adheres to a
"blue tech style" for a modern and professional aesthetic.
- 2. Capability Map (能力矩阵):
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Purpose: To illustrate the collective and individual strengths of installed skills across various domains.
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Mechanism: Utilizes a radar chart to visualize skill coverage in key capability areas such as Data Processing, Creative Writing, Technical Development, Logical Reasoning, and Communication. This helps users identify skill gaps or overlaps.
- 3. Contextual Prompting (智能联想提示):
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Purpose: To proactively suggest relevant skills based on user input, making skill discovery and activation seamless within OpenClaw or other Claw-like applications.
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Mechanism: Provides a retrieval mechanism for OpenClaw or current Claw-like applications to quickly match the most suitable installed skills when a user asks a question, prompting the user with options like: "您已安装的 [Skill名称] 具备处理此任务的能力,是否启用?"
Usage Instructions
To generate the skill dashboard, follow these steps:
- 1. Scan Installed Skills: Execute the
scan_skills.py script to gather data on all skills present in the /home/ubuntu/skills/ directory. This script parses each SKILL.md file to extract necessary metadata and performs a preliminary heuristic mapping of capabilities.
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The output will be a JSON array containing information for each skill, including its name, description, and a calculated capabilities score across different dimensions.
- 2. Generate Dashboard Visualization: Use the
dashboard_template.md along with the data obtained from scan_skills.py to render the final dashboard. The template is designed to dynamically populate the visual dashboard, capability map (mermaid radar chart), and contextual prompting examples.
The dashboard_template.md expects placeholders to be replaced with actual skill data. For the visual dashboard table, iterate through the scanned skill data. For the capability map, aggregate the capability scores from all skills to form a combined radar chart dataset. For contextual prompting, identify the top skills for each capability dimension.
Example of data integration for the template (conceptual):
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Bundled Resources
- -
scripts/scan_skills.py: A Python script to scan the /home/ubuntu/skills/ directory, parse SKILL.md files, extract metadata, and heuristically map skill capabilities. templates/dashboard_template.md: A Markdown template for generating the visual dashboard, including placeholders for skill information, a Mermaid radar chart for capability mapping, and examples for contextual prompting.
Design Considerations
- - UI/UX: The dashboard is designed with a "blue tech style" aesthetic, ensuring a clean, modern, and professional look that aligns with user preferences for web applications.
- Extensibility: The
scan_skills.py script can be easily extended to include more sophisticated parsing logic or integrate with a more robust capability taxonomy. - Interactivity: While the initial output is Markdown, the design is conducive to being rendered into an interactive web interface (e.g., using React components for cards and a charting library for the radar graph) for a richer user experience.
技能看板可视化器
本技能旨在通过提供清晰、交互且视觉吸引人的看板,汇总所有已安装技能的能力,从而增强OpenClaw用户体验。它解决了用户难以记住并充分利用其多样化技能集全部潜力的常见痛点。
核心功能
本技能整合了三大关键功能,为管理技能提供整体视图和交互模型:
- 1. 可视化看板:
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目的:快速概览每个已安装技能。
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机制:自动从SKILL.md文件中提取元数据(名称、描述)。每个技能以卡片形式呈现,包含图标、类别标签及其核心能力的简要摘要。设计遵循
蓝色科技风格,营造现代专业的视觉效果。
- 2. 能力矩阵:
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目的:展示已安装技能在各个领域的集体和个体优势。
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机制:利用雷达图可视化技能在关键能力领域的覆盖情况,如数据处理、创意写作、技术开发、逻辑推理和沟通交流。这有助于用户识别技能缺口或重叠。
- 3. 智能联想提示:
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目的:根据用户输入主动推荐相关技能,使技能发现和激活在OpenClaw或其他类Claw应用中无缝进行。
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机制:为OpenClaw或当前类Claw应用提供检索机制,当用户提问时快速匹配最合适的已安装技能,并向用户提示选项,例如:您已安装的 [Skill名称] 具备处理此任务的能力,是否启用?
使用说明
要生成技能看板,请按以下步骤操作:
- 1. 扫描已安装技能:执行scan_skills.py脚本,收集/home/ubuntu/skills/目录下所有技能的数据。该脚本解析每个SKILL.md文件以提取必要的元数据,并进行初步的启发式能力映射。
bash
python3 /home/ubuntu/skills/skill-dashboard-visualizer/scripts/scan_skills.py
输出将是一个JSON数组,包含每个技能的信息,包括名称、描述以及在不同维度上计算出的capabilities分数。
- 2. 生成看板可视化:使用dashboardtemplate.md模板以及从scanskills.py获取的数据来渲染最终看板。该模板设计用于动态填充可视化看板、能力矩阵(mermaid雷达图)和智能联想提示示例。
dashboard_template.md期望将占位符替换为实际技能数据。对于可视化看板表格,遍历扫描到的技能数据。对于能力矩阵,汇总所有技能的能力分数以形成组合雷达图数据集。对于智能联想提示,识别每个能力维度的顶级技能。
模板数据集成示例(概念性):
python
import json
import os
# 假设skillsdata来自scanskills.py
# skillsdata = json.loads(shelloutputfromscan_skills)
templatepath = /home/ubuntu/skills/skill-dashboard-visualizer/templates/dashboardtemplate.md
with open(template_path, r, encoding=utf-8) as f:
template_content = f.read()
# 填充可视化看板表格(简化示例)
dashboardtablerows = []
for skill in skills_data:
icon = 💡 # 占位符,理想情况下基于技能类型
name = skill.get(name, N/A)
description = skill.get(description, N/A)
use_cases = # 从描述或特定标签推导
dashboardtablerows.append(f| {icon} | {name} | {description} | {use_cases} |)
# 替换模板中的占位符
# templatecontent = templatecontent.replace(| {{icon}} | {{name}} | {{description}} | {{usecases}} |, \n.join(dashboardtable_rows))
# 填充能力矩阵(简化汇总)
totaldata = sum(s[capabilities].get(Data, 0) for s in skillsdata)
totalcreative = sum(s[capabilities].get(Creative, 0) for s in skillsdata)
totaltech = sum(s[capabilities].get(Technical, 0) for s in skillsdata)
totallogic = sum(s[capabilities].get(Logic, 0) for s in skillsdata)
totalcomm = sum(s[capabilities].get(Communication, 0) for s in skillsdata)
# templatecontent = templatecontent.replace(data: [{{datascore}}, {{creativescore}}, {{techscore}}, {{logicscore}}, {{comm_score}}],
# fdata: [{totaldata}, {totalcreative}, {totaltech}, {totallogic}, {total_comm}])
# 进一步替换智能联想提示...
# 最终渲染的dashboard_md可以显示或保存。
捆绑资源
- - scripts/scanskills.py:一个Python脚本,用于扫描/home/ubuntu/skills/目录,解析SKILL.md文件,提取元数据,并启发式映射技能能力。
- templates/dashboardtemplate.md:一个Markdown模板,用于生成可视化看板,包含技能信息占位符、用于能力映射的Mermaid雷达图以及智能联想提示示例。
设计考量
- - UI/UX:看板采用蓝色科技风格美学设计,确保干净、现代、专业的外观,符合用户对Web应用的偏好。
- 可扩展性:scan_skills.py脚本可以轻松扩展,以包含更复杂的解析逻辑或与更强大的能力分类体系集成。
- 交互性:虽然初始输出为Markdown,但该设计有利于渲染成交互式Web界面(例如,使用React组件制作卡片,使用图表库制作雷达图),以获得更丰富的用户体验。