air_train_ev
Unified travel + mobility skill: (1) flight pricing with Amadeus (flight offers), (2) public transport/train journey planning with Navitia (journeys, departures), and (3) find nearby EV charge points using Open Charge Map. Use when Alessandro asks for flight prices, train itineraries/schedules, or EV charging stations.
Best use case
air_train_ev is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Unified travel + mobility skill: (1) flight pricing with Amadeus (flight offers), (2) public transport/train journey planning with Navitia (journeys, departures), and (3) find nearby EV charge points using Open Charge Map. Use when Alessandro asks for flight prices, train itineraries/schedules, or EV charging stations.
Teams using air_train_ev should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/air-train-ev/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How air_train_ev Compares
| Feature / Agent | air_train_ev | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Unified travel + mobility skill: (1) flight pricing with Amadeus (flight offers), (2) public transport/train journey planning with Navitia (journeys, departures), and (3) find nearby EV charge points using Open Charge Map. Use when Alessandro asks for flight prices, train itineraries/schedules, or EV charging stations.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Air + Train + EV ## Credentials (env) Do not hardcode keys in scripts. ### Flights (Amadeus) - `AMADEUS_CLIENT_ID` - `AMADEUS_CLIENT_SECRET` - Optional: `AMADEUS_HOST` (default `https://api.amadeus.com`) ### Trains / public transport (Navitia) - `NAVITIA_TOKEN` - Optional: `NAVITIA_HOST` (default `https://api.navitia.io`) - Optional: `NAVITIA_COVERAGE` (default `sandbox`) ### EV charge points (Open Charge Map) - `OPENCHARGEMAP_API_KEY` - Optional: `OPENCHARGEMAP_HOST` (default `https://api.openchargemap.io`) ## Flights — quick usage ```bash python3 skills/air-train-ev/scripts/flight_offers.py \ --origin ZRH --destination IST \ --departure 2026-03-10 \ --adults 1 --travel-class ECO \ --non-stop true \ --included-airlines PC,VF,TK \ --max 6 ``` Output formatting is fixed: - Dates/times: `DD/MM/YY HH:MM` - EUR prices use `€` ## Train journeys — quick usage ```bash python3 skills/air-train-ev/scripts/navitia.py coverage python3 skills/air-train-ev/scripts/navitia.py places --q "Strasbourg" python3 skills/air-train-ev/scripts/navitia.py journeys --from "Strasbourg" --to "Rennes" --datetime "2026-03-07T08:00:00" --count 5 ``` ## EV charge points — quick usage ```bash python3 skills/air-train-ev/scripts/ev_charge_points.py \ --lat 48.5839 --lon 7.7455 \ --km 5 --max 10 ``` Notes: - This uses Open Charge Map `GET /v3/poi/`. - Returned results include operator/title, address, distance (when available), connector types, and coordinates.
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