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openclaw-bahnOpenClaw bahn 搜索

Agent Skill

openclaw-bahn 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:openclaw-bahn(OpenClaw bahn 搜索)
来源仓库:https://github.com/ableitung/openclaw-bahn
安装命令:
openclaw skills install openclaw-bahn
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install openclaw-bahn

简介

集成德国铁路列车实时追踪与时刻查询命令集。

  • 支持按车次、站点或时间检索列车运行状态。openclaw-bahn 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 返回延误信息、换乘建议与票务余量等实用数据。
  • 依赖 DB Navigator 或官方数据接口,需注册开发者账号。
  • 主要用于出行规划辅助,不保证绝对准确性。

SKILL.md

name
bahn
description
A comprehensive suite of commands for tracking Deutsche Bahn trains
version
1.0.0
metadata
openclaw
requires
bins
install
package
db-vendo-client
package
devalue
package
fast-xml-parser
emoji
🚆
homepage
https://github.com/ableitung/openclaw-bahn
os

Bahn

A comprehensive suite of commands for Deutsche Bahn trains - live departures, delay tracking, Baustellen/disruption alerts, journey planning, connection parsing, historical delay stats, and delay predictions. No API keys needed.

Flags

FlagWhat it doesWhen to use
--predictRuns the exponential delay model (transferProb, zugbindungProb)User asks about probability of catching a transfer or Zugbindung being lifted
--statsFetches historical bahn.expert aggregate data per trainUser asks about historical delay patterns for a specific train

Examples

# Search for a train station
node scripts/bahn.mjs --search "Wuppertal" [--json]

# Find latest departures from a given station
node scripts/bahn.mjs --departures "Wuppertal Hbf" [--results N] [--json]

# Default: Parse and show live data
echo '<raw Navigator share text>' | node scripts/bahn.mjs --parse [--json]

# With prediction model (transferProb, zugbindungProb)
echo '<text>' | node scripts/bahn.mjs --parse --predict [--json]

# With historical stats from bahn.expert
node scripts/bahn.mjs --parse connections/active.json --stats [--json]

# Both
node scripts/bahn.mjs --parse connections/active.json --predict --stats [--json]

# Find a given journey in timetable
node scripts/bahn.mjs --journey "From" "To" [--date YYYY-MM-DD] [--time HH:MM] [--results N] [--days N] [--json]

# Get current delays
node scripts/bahn.mjs --live --current-leg N [--delay M] connections/active.json [--json]

# Find a specific train by number and category (example: ICE 933)
node scripts/bahn.mjs --category CAT --train NUM [--date YYYY-MM-DD] [--json]

File Layout

scripts/
├── bahn.mjs                    ← thin CLI dispatcher (~60 lines)
├── lib/
│   ├── commands/             ← one module per mode
│   │   ├── search.mjs        ← --search: station lookup
│   │   ├── departures.mjs    ← --departures: live departure board
│   │   ├── parse.mjs         ← --parse: connection parsing + enrichment
│   │   ├── journey.mjs       ← --journey: route search
│   │   ├── live.mjs          ← --live: real-time transfer check
│   │   └── track.mjs         ← --track: train tracking
│   ├── helpers.mjs           ← shared helpers (envelope, transfers, assessment)
│   ├── data.mjs              ← source router (IRIS/Vendo/bahn.expert)
│   ├── predict.mjs           ← probability model (opt-in via --predict)
│   ├── stats.mjs             ← delay profiles + historical stats (opt-in via --stats)
│   ├── parse.mjs             ← connection text parser
│   ├── format.mjs            ← output formatter
│   ├── messageLookup.mjs     ← IRIS delay code lookup
│   └── sources/
│       ├── bahn-expert.mjs   ← bahn.expert tRPC source
│       ├── iris.mjs          ← IRIS XML source
│       └── vendo.mjs         ← db-vendo-client source

JSON Envelope

All modes support --json:

{
  "mode": "string",
  "timestamp": "ISO8601",
  "connection": { "date", "from", "to", "legs", "transfers" },
  "journeyOptions": { "from", "to", "date", "options" },
  "departures": { "station", "entries" },
  "stations": { "query", "results" },
  "liveStatus": { "currentLeg", "nextTransfer", "zugbindungStatus", "recommendation", "remainingTransfers" },
  "trackStatus": { "train", "from", "to", "stops", "maxDelay", "zugbindungStatus" },
  "assessment": null,
  "errors": [],
  "warnings": []
}

The assessment field is only populated when --predict is used. Without it, assessment is null.

Prediction Model (predict.mjs) — opt-in only

Exponential delay distributions per train category. Only loaded when --predict is passed.

CategoryMean delayCancel rate
ICE5.0min5.5%
IC/EC4.0min4.0%
RE2.5min2.0%
RB2.0min1.5%
S1.5min1.0%
Bus3.0min2.0%

P(Zugbindung triggered) per leg = exp(-20/mean). Overall P(Zugbindung) = 1 - ∏(1 - P(leg_i ≥ 20min)).

Coverage

Long-distance (ICE/IC/EC), regional (RE/RB), S-Bahn, buses, and international trains to neighboring countries.

Report issues and legal information here: https://github.com/ableitung/openclaw-bahn

适合场景

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OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

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需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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安装前确认

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