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// Skill profile

Route Assistant (route-assistant)

name: route-assistant

by chandler0714 · published 2026-03-22

数据处理API集成加密货币
Total installs
0
Stars
★ 0
Last updated
2026-03
// Install command
$ claw add gh:chandler0714/chandler0714-route-assistant
View on GitHub
// Full documentation

---

name: route-assistant

description: Intelligent route planning assistant with optimized display. Three-part output: transport options table, recommended schemes, and important reminders.

metadata:

openclaw:

emoji: 🗺️

triggers:

- 怎么去

- 路线

- 距离

- 多远

- 出行

- 公交

- 开车

- 步行

- 打车

- 地址

- 哪里

- how to get

- route

- distance

- transit

- driving

---

# Route Assistant (route-assistant)

An intelligent travel route planning assistant with optimized three-part output structure using Amap (高德地图) API.

Output Structure

Part 1: 出行方式一览 (Transport Options Table)

Shows all available transport methods in table format:

| 出行方式 | 距离 | 耗时 | 明细 |

|---------|------|------|------|

| 🚗 驾车 | 22.6公里 | 33分钟 | 自驾前往 |

| 🚌 公交 | 22.4公里 | 45分钟 | 公共交通 |

| 🚕 打车 | 22.6公里 | 40分钟 | 出租车/网约车 |

| 🚶 步行 | 961米 | 10分钟 | 徒步 |

Part 2: 推荐方案 (Recommended Schemes)

Sorted by travel time, filters infeasible options:

  • Driving: Always shown
  • Transit: Only if available
  • Taxi: Only if distance > 1km
  • Walking: Only if distance ≤ 3km
  • Part 3: 重要提醒 (Important Reminders)

    When train/flight info is provided:

  • Shows departure/arrival times
  • Calculates suggested departure time
  • Warns if travel time conflicts with departure time
  • Features

    1. **Smart Recognition** - Automatically extracts origin and destination

    2. **Three-Part Output** - Structured display for clarity

    3. **Intelligent Filtering** - Filters infeasible options

    4. **Time Conflict Detection** - Warns if can't make it on time

    Query Examples

  • "从XX到XX怎么去?"
  • "坐G106车从XX到XX"
  • "天安门到故宫怎么走"
  • Technical Details

  • Uses Amap Geocoding API
  • Uses Amap Direction API v5
  • Duration estimated based on distance (v5 doesn't return duration)
  • Smart filtering based on distance thresholds
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