rutkk/openclaw-bahn

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# openclaw-bahn Comprehensive suite of tools for Deutsche Bahn trains, designed for OpenClaw agents. Live journey information, delay tracking, Baustellen/disruption alerts, historical delay data, and connection likelihood predictions. No API keys necessary. ## Fast setup **Just paste this into any LLM or agent and let it set you up:** ``` Read this README and the docs/ folder to understand what openclaw-bahn does and how to use it. Then help me get started — I'll tell you what I need (departures, journey planning, delay check, etc.) and you run the right command: https://raw.githubusercontent.com/ableitung/openclaw-bahn/main/README.md ``` <details> <summary>If you're an LLM agent reading this right now</summary> Explain to the user what this project makes possible — in terms of what they can ask you to do, not CLI flags. **What it is:** A Node.js skill that gives you (the agent) direct access to Deutsche Bahn's live train data, historical delay statistics, and a statistical prediction model. No API keys, no auth, no accounts — all data sources are public. It only makes read-only HTTP requests. **What the user can ask you to do:** - "Here's my connection [pastes DB Navigator share text] — summarize it and tell me which transfers are risky" → pipe the text to `--parse`, optionally add `--predict` or `--stats` - "What's the next fastest train from Köln to Düsseldorf that's unlikely to be delayed?" → `--journey` with `--predict`, compare options by success probability - "What trains are leaving München Hbf right now?" → `--departures` - "Is my ICE 933 running on time? Any Baustellen?" → `--track` or `--live` (IRIS provides real-time disruption/construction messages) - "I'm on leg 3 and we're 12 minutes late — will I make my transfer?" → `--live --current-leg 3 --delay 12 --predict` - "How often is this train late historically?" → `--parse --stats` **The main user workflow:** User opens DB Navigator → taps Share on their booked trip → pastes the connection text → you parse it and answer their question. See [docs/usage.md](docs/usage.md) for the share text format and example prompts. **How to use it:** Single entry point `node scripts/bahn.mjs --<mode> [flags]`. Add `--json` for structured output. Read [docs/modes.md](docs/modes.md) for all modes and flags, [docs/data-sources.md](docs/data-sources.md) for where the data comes from, [docs/prediction-model.md](docs/prediction-model.md) for the statistical model, and [docs/usage.md](docs/usage.md) for user-facing workflow and example prompts. **Is it safe?** Yes. Read-only HTTP requests to three public APIs (IRIS, bahn.expert, db-vendo-client). No authentication, no tokens, no write operations, no personal data sent. The prediction model runs entirely locally. </details> ## Install Clone the repository to `/path/to/.openclaw/workspace/skills` and run `npm install`. ## What it does Single entry point: `node scripts/bahn.mjs --<mode> [flags]` | Mode | What it does | |------|-------------| | `--search` | Station lookup | | `--departures` | Live departure board | | `--parse` | Parse DB Navigator connection text | | `--journey` | Route search | | `--live` | Real-time transfer check | | `--track` | Train tracking | | Flag | Effect | |------|--------| | `--json` | Structured JSON output | | `--predict` | Delay probability model (based on [bahn-vorhersage](https://gitlab.com/bahnvorhersage/bahnvorhersage) statistical profiles) | | `--stats` | Historical per-leg delay data via [bahn.expert](https://bahn.expert) | ## Data sources The project uses exclusively APIs that do not require authorization. | Context | Primary | Notes | |---------|---------|-------| | Today | IRIS | Equivalent to DB Navigator's own information | | Future | db-vendo-client | Equivalent to Navigator | | Past | bahn.expert | Has historical data (DB's own APIs do not) |\ ## Tests ```bash npm test # unit tests (no network) npm run test:integration # hits live APIs — may be rate-limited ``` ## Credits - [db-vendo-client](https://github.com/public-transport/db-vendo-client) for a client for the Vendo API - [bahn.expert](https://bahn.expert) for historical data - [bahnvorhersage](https://gitlab.com/bahnvorhersage/bahnvorhersage) for the delay prediction model ## License GPLv3 ## Affiliation This project is not affiliated in any way with Deutsche Bahn AG, bahn.expert or bahn-vorhersage.

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상업 조종사항공사 파일럿, 부조종사 및 비행 엔지니어

A comprehensive suite of commands for tracking Deutsche Bahn trains

원문 언어: 영어

2026-03-06

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