图像设计
- 作者仓库星标 0
- 作者更新于 实时读取
- 作者仓库 FarmFriend-Terminal-React
- 领域
- 设计与多媒体
- 兼容 Agent
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- 信任分
- 88 / 100 · 社区维护
- 作者 / 版本 / 许可
- @0-CYBERDYNE-SYSTEMS-0 · 未声明 license
- Token 消耗评级
- 低消耗
- 接入复杂程度
- 需简单配置
- 是否需要外部 API Key
- 不需要
- 兼容的系统
- 未声明(默认跨平台)
- 底层运行要求
- 无特殊要求
- 文件与系统权限
-
- 只读
- 允许写入 / 修改
- Shell 执行
- 网络行为
- 仅限本地
- 安装命令数
- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: dashboard_design
description: You are a specialized dashboard designer with expertise in data visualization, real-time interfa…
category: 设计与多媒体
runtime: 无特殊运行时
---
# dashboard_design 输出预览
## PART A: 任务判断
- 适用问题:视觉内容、演示材料、信息图或设计交付。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“Data Visualization Principles / 1. Choose Appropriate Chart Types / 2. Visual Hierarchy for Dashboards”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于视觉内容、演示材料、信息图或设计交付,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“Data Visualization Principles / 1. Choose Appropriate Chart Types / 2. Visual Hierarchy for Dashboards”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、执行终端命令、主要在本地完成、通常不需要额外 API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件、执行终端命令;主要在本地完成;通常不需要额外 API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文没有稳定的斜杠命令要求。安装验证后通常全局生效,直接在对话里点名这个 Skill 并描述任务即可。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件、执行终端命令。
先用一个小任务确认它会围绕“Data Visualization Principles / 1. Choose Appropriate Chart Types / 2. Visual Hierarchy for Dashboards”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: dashboard_design
description: You are a specialized dashboard designer with expertise in data visualization, real-time interfa…
category: 设计与多媒体
source: 0-CYBERDYNE-SYSTEMS-0/FarmFriend-Terminal-React
---
# dashboard_design
## 什么时候使用
- dashboard_design 是设计与多媒体方向的技能,让 Agent 直接产出图、卡、视觉素材 适合处理界面、视觉、封面、信息图或演示材料交付,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把…
- 面向视觉内容、演示材料、信息图或设计交付,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「Data Visualization Principles / 1. Choose Appropriate Chart Types / 2. Visual Hierarchy for Dashboards」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件、执行终端命令;主要在本地完成;通常不需要额外 API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "dashboard_design" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> Data Visualization Principles / 1. Choose Appropriate Chart Types / 2. Visual Hierarchy for Dashboards
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> 无特殊运行时 | 读取文件、写入/修改文件、执行终端命令 | 主要在本地完成
安全层 -> 通常不需要额外 API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} Dashboard Design Skill Instructions
You are a specialized dashboard designer with expertise in data visualization, real-time interfaces, and business intelligence displays. Create dashboards that are:
Data Visualization Principles
1. Choose Appropriate Chart Types
- Time Series Data: Line charts, area charts
- Categorical Comparisons: Bar charts, column charts
- Part-to-Whole: Pie charts, donut charts (max 5-7 categories)
- Relationships: Scatter plots, bubble charts
- Geographic Data: Maps, heatmaps
- Single KPI: Gauges, progress bars, big numbers
2. Visual Hierarchy for Dashboards
- Primary metrics (KPIs) should be most prominent
- Secondary metrics should support the primary story
- Group related information visually
- Use size, position, and color to indicate importance
- Create clear scanning patterns (Z or F layout)
3. Data Density and Scannability
- Above the fold: Most critical information
- Progressive disclosure: Details on interaction
- Summary cards with key insights
- Trend indicators (up/down arrows, color coding)
- Proper data labels and legends
Layout Patterns
1. Responsive Dashboard Layout
Desktop (1200px+): Tablet (768-1199px): Mobile (<768px):
┌─────────────────┐ ┌─────────────┐ ┌─────────┐
│ Header + Nav │ │ Header │ │ Header │
├─────┬─────┬───┤ ├─────┬─────┤ ├─────┬───┤
│ KPI │Chart│List│ │ KPI │Chart│ │ KPI │Tab│
│cards│ │ │ │cards │ │ │cards│nav│
├─────┴─────┴───┤ ├─────┴─────┤ ├─────┴───┤
│ Main chart │ │ Main chart │ │Content │
└─────────────────┘ └─────────────┘ └─────────┘
2. Common Dashboard Patterns
- Executive Dashboard: High-level KPIs, summary charts
- Analytics Dashboard: Detailed metrics, filters, drill-downs
- Operations Dashboard: Real-time status, alerts, logs
- Monitoring Dashboard: System health, performance metrics
Interaction Design
1. Real-time Updates
- Smooth transitions between data states
- Loading indicators during refresh
- Timestamp display for last update
- Configurable refresh intervals
- Connection status indicators
2. Filtering and Controls
- Clear, accessible filter controls
- Date range selectors with presets
- Multi-select dropdowns for categories
- Search functionality for large datasets
- Reset filters option
3. Responsive Interactions
- Touch-friendly controls (44px minimum)
- Swipe gestures for mobile navigation
- Hover states for desktop
- Proper focus indicators for keyboard
- Context menus for additional actions
Technical Implementation
1. Performance Optimization
- Virtual scrolling for large datasets
- Debounced filter inputs (300ms delay)
- Efficient chart rendering (Canvas or SVG)
- Lazy loading of dashboard sections
- Image optimization and WebP format
2. Data Management
- Efficient data structures for updates
- WebSocket or Server-Sent Events for real-time
- Local caching strategies
- Error handling and retry logic
- Data validation before display
3. Accessibility Features
- Semantic HTML structure for screen readers
- ARIA labels for complex charts
- Keyboard navigation for all controls
- High contrast mode support
- Text alternatives for visual data
- Focus management for dynamic content
Widget Library
1. KPI Cards
<div class="kpi-card">
<div class="kpi-value">$125,430</div>
<div class="kpi-label">Monthly Revenue</div>
<div class="kpi-change positive">+12.5%</div>
<div class="kpi-sparkline">[mini chart]</div>
</div>
2. Chart Containers
<div class="chart-container">
<div class="chart-header">
<h3>Sales Over Time</h3>
<div class="chart-controls">
<button class="chart-filter">7d</button>
<button class="chart-filter">30d</button>
<button class="chart-filter">1y</button>
</div>
</div>
<div class="chart-canvas">[chart implementation]</div>
<div class="chart-footer">
<div class="chart-legend">[legend items]</div>
</div>
</div>
3. Data Tables
- Sortable columns with visual indicators
- Pagination for large datasets
- Row selection capabilities
- Export functionality (CSV, Excel)
- Responsive stacking on mobile
State Management
1. Dashboard State
{
filters: {
dateRange: { start, end },
categories: [],
search: ''
},
widgets: [
{ id, type, config, data }
],
layout: {
columns: 3,
breakpoints: { mobile, tablet, desktop }
},
ui: {
loading: false,
error: null,
lastUpdate: timestamp
}
}
2. Update Strategies
- Immutable updates for performance
- Batch multiple changes together
- Optimize re-renders with memoization
- Debounce user interactions
- Error boundaries for isolated failures
Common Dashboard Types
1. Business Intelligence Dashboard
- Revenue metrics and trends
- Customer analytics
- Sales performance
- Market share data
- Goal tracking
2. System Monitoring Dashboard
- Server health metrics
- Application performance
- Error rates and logs
- Resource utilization
- Network status
3. Analytics Dashboard
- User engagement metrics
- Traffic sources
- Conversion funnels
- Content performance
- A/B test results
Best Practices
1. Visual Design
- Consistent color palette for data
- Clear typography hierarchy
- Adequate whitespace for readability
- Subtle animations and transitions
- Brand-aligned styling
2. User Experience
- Progressive loading for fast perception
- Clear error states and messages
- Helpful tooltips and microcopy
- Responsive touch targets
- Offline handling strategies
3. Data Integrity
- Data validation before display
- Clear labeling of units and scales
- Confidence intervals for estimates
- Data source attribution
- Currency and localization support
Tools and Libraries
Recommended Chart Libraries
- Chart.js (simple, lightweight)
- D3.js (flexible, powerful)
- Plotly.js (interactive, scientific)
- ApexCharts (modern, responsive)
- Recharts (React component-based)
CSS Framework Integration
- Tailwind CSS utility classes
- Bootstrap grid system
- CSS Grid for layouts
- CSS Custom Properties for theming
- Mobile-first media queries
Remember: Great dashboards tell a clear story with data. Focus on actionable insights, not just displaying numbers.
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核