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malkreide
by malkreide

road_multimodal_plan

Read-only

Plan a multimodal route from your car's location to any destination: get the nearest station, Park & Rail options, and train connections in one step-by-step plan.

Instructions

Plan a multimodal trip: Drive → Park & Rail → Train → Destination.

The «Holy Grail» of Phase 3: combines all data sources into a complete door-to-door multimodal route plan.

Workflow (all in parallel where possible):

  1. Find the nearest train station from your start location

  2. Find Park & Rail facilities near the start (where to park your car)

  3. Get public transport connections from nearest station to destination

  4. Check shared mobility options at start for last-mile to station

  5. Assemble everything into a step-by-step route plan

Use case: «I'm in Dietikon with a car. I need to get to Bern. Where can I park? Which train should I take?»

No API key required – uses:

  • SBB Open Data (Park & Rail) – free

  • transport.opendata.ch (PT connections) – free

  • sharedmobility.ch (sharing options) – free

Data sources:

  • SBB Open Data Portal (data.sbb.ch) – Park & Rail

  • transport.opendata.ch – Journey planning

  • sharedmobility.ch – Sharing last mile

Returns: JSON with: - nearest_station: Closest train station from start - recommended_park_rail: Best P+R option - plan_steps: Step-by-step multimodal route - all_ov_connections: All available PT connections - last_mile_sharing: Sharing options at start location

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds extensive behavioral context beyond annotations: it outlines the parallel workflow, lists data sources (with no API key required), describes the return format, and explains the process. Annotations already indicate readOnlyHint=true, and the description is consistent with that.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with a summary but is excessively verbose, repeating data sources twice and including a multi-step workflow that could be condensed. While structured, it contains unnecessary repetition, reducing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (multimodal planning with multiple data sources), the description covers all necessary aspects: input parameters, workflow, data sources, return format, and a use case. The output schema exists, so return values are further clarified. The description is complete for an agent to understand the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides detailed descriptions for each parameter (in German), including constraints and examples. The description does not add significant new semantic information beyond the schema; it only reinforces examples. Baseline 3 is appropriate given schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool plans a multimodal trip with a specific sequence (Drive → Park & Rail → Train → Destination). It distinguishes itself from sibling tools by emphasizing it combines all data sources into a complete door-to-door plan, and provides a concrete use case example.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes a workflow and a use case ('I'm in Dietikon with a car...'), giving clear context for when to use the tool. However, it does not explicitly state when not to use it or mention alternative sibling tools for simpler tasks, so it lacks complete exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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