8.3
/ 10
1 evaluations
1.7k Downloads
Overview
Provide live public-transport journey planning and next-departure information for Berlin (BVG network) using the v6.bvg.transport.rest API. The skill resolves stops/addresses, queries journeys with depart-at/arrive-by constraints, and returns 2–3 concise, step-by-step route options plus refresh tokens for updates.
Key Advantages
1.Specialized for Berlin’s BVG system, leveraging the official v6.bvg.transport.rest API for relatively up-to-date routing and departure data.
2.Supports both ‘depart at’ and ‘arrive by’ planning, which is crucial for time-sensitive itineraries (appointments, flights, events).
3.Produces 2–3 ranked journey options with clear trade-offs (time, transfers, walking), improving decision-making vs a single opaque suggestion.
4.Includes step-by-step instructions (walk segments, lines, directions, platforms when available) suitable for direct user presentation.
5.Can return machine-friendly JSON structures (journey IDs, refreshTokens, legs) for downstream tools or UI layers to refresh and visualize journeys in real time.
Use Cases
- Planning a BVG journey between two Berlin addresses or POIs, including mixed U-Bahn/S-Bahn/bus/tram routes with clear transfer points.
- Checking next departures from a specific stop or station (e.g., “When is the next U-Bahn from U Rosenthaler Platz?”).
- Time-targeted travel planning where the user must arrive at a destination by a given time (arrive-by journeys).
- Comparing a few alternative routes based on duration, walking distance, and number of transfers to pick the most suitable option.
- Integrating live BVG route suggestions into a Berlin-focused assistant, travel planner, or concierge experience that needs both human-readable text and structured journey data.
Evaluation Scores
8.3
/ 10
Reliability
7.3
Functionality
8.0
Usability
8.6
Safety
9.2
Performance
8.2
Compatibility
8.5
Based on 1 evaluation · Latest: 3/19/2026
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Evaluation History (1)
8.3/103/19/2026▼
OS: darwin-arm64LLM: arcee-ai/trinity-large-preview
**Quick judgment**
A strong, domain-specific skill for **Berlin BVG public transport routing**. It’s well-scoped, uses the official v6.bvg.transport.rest API, and is suitable as the default choice whenever a user in Berlin asks for public-transport directions, next departures, or arrive-by/depart-at planning.
**What it does well**
- Resolves locations/stops and calls `/journeys` to produce 2–3 route options, emphasizing total time, transfers, and walking.
- Handles both **depart-at** and **arrive-by** queries, which is important for practical trip planning.
- Provides **step-by-step instructions** (walk → board line X toward Y → get off at stop B → walk), plus optional machine-readable JSON including `refreshToken` for real-time updates.
- Implements BVG-specific nuances (IBNR base codes, URL-encoding), which are common sources of bugs in naive integrations.
**Main risks / limitations**
- **Geographic scope:** Only appropriate for Berlin/BVG; using it elsewhere will fail or yield irrelevant results. The calling agent must ensure the user is asking about Berlin-area public transport.
- **External API dependence:** Reliability and latency depend on the public BVG API. Rate limits, outages, or schema changes could cause degraded performance or failures.
- **Ambiguous locations:** Fuzzy address or stop names may need disambiguation; if the skill or calling agent doesn’t clarify, routes could start/end at unintended stops.
- **Coverage constraints:** Focused on BVG; non-BVG or long-distance rail may be incomplete or absent depending on the BVG API’s scope.
**Recommended scenarios to use this skill**
- User is in Berlin and asks: “How do I get from [address/POI] to [address/POI] by public transport?”
- User asks for **next departures** from a known Berlin stop/station.
- User specifies timing constraints: “Arrive at [place] by [time]” or “Depart after [time]” within Berlin.
- A Berlin-focused assistant needs both **human-readable directions** and **structured journey data** for UI rendering or live-refresh features.
Overall, this skill is a good fit as the **go-to BVG route/next-departure planner** within a Berlin context, with strong usability and safety and moderate but acceptable reliability given its reliance on a third-party API.
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