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Traffic Lights

核心功能是根据场景选择合适的可视化类型(红绿灯、哈维球等),完成多维度评估对比,还可生成量化评分、模式分析及决策建议。典型场景包括竞品对比、方案选型、项目健康监控、差距分析等。输入为评估维度与对比选项,输出为结构化的评估图表及相关分析内容。

linuszz
linuszz
热度 42.90
最近更新 2026-05-11 17:35:11
分类:数据依赖:纯提示词应用场景:数据处理 / 报告撰写 / 市场分析

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add traffic-lights
Metadata
name
traffic-lights
description
Create multi-criteria comparison charts using traffic lights or Harvey balls. Use for option evaluation, competitive comparison, and executive dashboards.

Traffic Light Charts

Metadata

  • Name: traffic-lights
  • Description: Multi-criteria assessment visualization
  • Triggers: traffic light, harvey ball, stoplight, RAG status, multi-criteria

Instructions

You are creating a traffic light chart to evaluate $ARGUMENTS.

Your task is to compare options across multiple criteria using a simple, visual format.

Framework

Visual Options

Traffic Lights (RAG)

🟢 Green = Good / On track / Above target
🟡 Yellow/Amer = Caution / At risk / Near target
🔴 Red = Bad / Off track / Below target

Harvey Balls (Half-moons)

○  Empty    = 0% / None / Very poor
◔  Quarter  = 25% / Below average
◑  Half     = 50% / Average
◕  Three-Q  = 75% / Above average
●  Full     = 100% / Excellent

Arrows

↑↑ Strong positive
↑   Positive
→   Neutral
↓   Negative
↓↓  Strong negative

When to Use Which

Chart Type Best For
Traffic Lights Status, progress, alerts
Harvey Balls Gradual comparison, rating
Arrows Trends, momentum
Stars Customer ratings, reviews
Numbers Precision needed

Standard Applications

  1. Competitive Comparison - Us vs. competitors on key criteria
  2. Option Evaluation - Compare alternatives for decision
  3. Status Dashboard - Project/portfolio health
  4. Gap Analysis - Current vs. desired state
  5. Vendor Selection - Compare suppliers on requirements

Output Process

  1. Define criteria - What dimensions matter?
  2. Set scale - What does each color/symbol mean?
  3. Gather data - Assess each option on each criterion
  4. Apply ratings - Consistent methodology
  5. Calculate overall - Summary score
  6. Visualize - Create the chart
  7. Annotate - Add context and insights
  8. Interpret - Draw conclusions

Output Format

## Traffic Light Chart: [Subject]

### Assessment Criteria

| # | Criterion | Weight | Definition |
|---|-----------|--------|------------|
| 1 | [Criterion 1] | 20% | 🟢=X, 🟡=Y, 🔴=Z |
| 2 | [Criterion 2] | 15% | 🟢=X, 🟡=Y, 🔴=Z |
| 3 | [Criterion 3] | 25% | 🟢=X, 🟡=Y, 🔴=Z |
| 4 | [Criterion 4] | 15% | 🟢=X, 🟡=Y, 🔴=Z |
| 5 | [Criterion 5] | 10% | 🟢=X, 🟡=Y, 🔴=Z |
| 6 | [Criterion 6] | 15% | 🟢=X, 🟡=Y, 🔴=Z |
|   | **Total** | **100%** | |

---

### Traffic Light Matrix

| Criterion | Option A | Option B | Option C | Option D |
|-----------|----------|----------|----------|----------|
| **1. [Criterion 1]** | 🟢 | 🟡 | 🟢 | 🔴 |
| **2. [Criterion 2]** | 🟡 | 🟢 | 🟡 | 🟡 |
| **3. [Criterion 3]** | 🟢 | 🔴 | 🟢 | 🟢 |
| **4. [Criterion 4]** | 🟢 | 🟢 | 🟡 | 🟡 |
| **5. [Criterion 5]** | 🟡 | 🟢 | 🔴 | 🟢 |
| **6. [Criterion 6]** | 🔴 | 🟡 | 🟢 | 🟡 |
| **OVERALL** | 🟢 | 🟡 | 🟢 | 🟡 |

**Legend:**
- 🟢 Green = Strong / Meets requirements
- 🟡 Yellow = Moderate / Partially meets
- 🔴 Red = Weak / Does not meet

---

### Scoring (Optional Quantitative)

| Criterion | Weight | Option A | Option B | Option C | Option D |
|-----------|--------|----------|----------|----------|----------|
| 1. [Criterion] | 20% | 3 (0.6) | 2 (0.4) | 3 (0.6) | 1 (0.2) |
| 2. [Criterion] | 15% | 2 (0.3) | 3 (0.45) | 2 (0.3) | 2 (0.3) |
| 3. [Criterion] | 25% | 3 (0.75) | 1 (0.25) | 3 (0.75) | 3 (0.75) |
| 4. [Criterion] | 15% | 3 (0.45) | 3 (0.45) | 2 (0.3) | 2 (0.3) |
| 5. [Criterion] | 10% | 2 (0.2) | 3 (0.3) | 1 (0.1) | 3 (0.3) |
| 6. [Criterion] | 15% | 1 (0.15) | 2 (0.3) | 3 (0.45) | 2 (0.3) |
| **WEIGHTED TOTAL** | **100%** | **2.45** | **2.15** | **2.50** | **2.15** |
| **RANK** | | **2nd** | **3rd** | **1st** | **3rd** |

*Scale: 1=Red, 2=Yellow, 3=Green*

---

### Alternative: Harvey Ball Format

| Criterion | Option A | Option B | Option C | Option D |
|-----------|----------|----------|----------|----------|
| **1. [Criterion]** | ● | ◑ | ● | ◔ |
| **2. [Criterion]** | ◑ | ● | ◑ | ◑ |
| **3. [Criterion]** | ● | ○ | ● | ◑ |
| **4. [Criterion]** | ● | ● | ◑ | ◑ |
| **5. [Criterion]** | ◑ | ● | ◔ | ● |
| **6. [Criterion]** | ◔ | ◑ | ● | ◑ |
| **OVERALL** | ◕ | ◑ | ● | ◑ |

**Legend:**
- ○ None (0%) | ◔ Quarter (25%) | ◑ Half (50%) | ◕ Three-Q (75%) | ● Full (100%)

---

### Pattern Analysis

**Strengths by Option**

| Option | Key Strengths | Key Weaknesses |
|--------|---------------|----------------|
| Option A | [Criterion 1, 3, 4] | [Criterion 6] |
| Option B | [Criterion 2, 4, 5] | [Criterion 3] |
| Option C | [Criterion 1, 3, 6] | [Criterion 5] |
| Option D | [Criterion 1, 3, 5] | [Criterion 1] |

**Patterns Observed**
1. [Pattern 1 - e.g., "All options score well on Criterion 4"]
2. [Pattern 2 - e.g., "Criterion 3 shows largest differentiation"]
3. [Pattern 3 - e.g., "No option scores green on all criteria"]

---

### Recommendation

**Top Choice: [Option C]**
- Rationale: [Why this option]
- Trade-offs: [What we give up]

**Runner-up: [Option A]**
- When to consider: [Situations where this is better]

**Not Recommended: [Option D]**
- Why not: [Key deficiencies]

Tips

  • Define criteria before rating - don't retrofit
  • Be consistent - same assessor or calibrated team
  • Don't have too many criteria (6-10 is optimal)
  • Weight criteria by importance
  • Use supporting data in appendix
  • The overall score should be a guide, not a rule
  • Patterns matter more than individual cells
  • Document the rationale for each rating

References

  • Few, Stephen. Information Dashboard Design. 2006.
  • Tufte, Edward. Beautiful Evidence. 2006.