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vehicle_generation_tool

Generate vehicles for SUMO simulation by specifying source and destination locations, with optimal path calculation and support for road names or geocoding.

Instructions

Add vehicles from source to destination with optimal path calculation.

SUPPORTS TWO MODES:

1. Road Name Mode:
   - Use exact road names (e.g., '테헤란로', '강남대로')
   - Set use_geocoding=False (default)

2. Location Mode (Recommended):
   - Use any location name or place (e.g., '강남역', '코엑스', 'Gangnam Station, Seoul')
   - Uses geocoding to find coordinates, then finds nearest edges
   - Set use_geocoding=True
   - Automatically validates if location is within network bounds

IMPORTANT NOTES:
- Location Mode validates coordinates against network bounds (1km buffer)
- If location is outside network, you'll get a clear error with network bbox info
- Search radius is 300m by default (sufficient for most cases)

Args:
    route_file: Route file path
    net_file: Network file path
    source_location: Source location (road name OR place name)
    destination_location: Destination location (road name OR place name)
    vehicle_id: Vehicle ID prefix (default: "genveh_0")
    depart_time: Departure time in seconds (default: 0.0)
    depart_time_range: Departure time range [min, max] in seconds (optional)
    vehicle_count: Number of vehicles to generate (default: 1)
    output_dir: Output directory for results
    use_geocoding: If True, use location-based mode with geocoding (default: False)
    search_radius: Search radius in km for nearest edge (default: 0.3 = 300m)

Examples:
    Road name mode:
    vehicle_generation_tool(
        route_file="routes.rou.xml",
        net_file="gangnam.net.xml",
        source_location="테헤란로",
        destination_location="강남대로",
        use_geocoding=False
    )

    Location mode (RECOMMENDED):
    vehicle_generation_tool(
        route_file="routes.rou.xml",
        net_file="gangnam.net.xml",
        source_location="강남역",
        destination_location="코엑스",
        use_geocoding=True,
        vehicle_count=20
    )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
net_fileYes
output_dirNooutput/trips
route_fileYes
vehicle_idNogenveh_0
depart_timeNo
search_radiusNo
use_geocodingNo
vehicle_countNo
source_locationYes
depart_time_rangeNo
destination_locationYes
Behavior3/5

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

The description discloses key behaviors like coordinate validation and error messages, but it does not mention whether files are created or overwritten, or any side effects. With no annotations, the description carries the full burden, and it falls short of fully disclosing behavioral traits.

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

Conciseness5/5

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

The description is well-structured with clear sections (purpose, modes, important notes, args, examples). It is front-loaded with the core purpose and efficiently uses bullet points and code blocks. No unnecessary information.

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 (11 parameters, two modes, no output schema) and lack of annotations, the description is remarkably complete. It covers modes, parameters, validation, examples, and error handling, making it fully actionable for an AI agent.

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

Parameters5/5

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

Since the input schema has 0% description coverage, the description effectively explains all parameters with defaults, meanings, and examples. It provides clear semantics for complex parameters like use_geocoding and search_radius, enabling correct usage.

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 the tool's purpose: 'Add vehicles from source to destination with optimal path calculation.' It then elaborates with two distinct modes (Road Name and Location), making it easy to understand the tool's unique functionality relative to sibling tools.

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 provides explicit guidance on when to use each mode (e.g., 'Location Mode (Recommended)') and offers important notes on validation and error handling. However, it lacks direct comparisons with sibling tools, leaving some ambiguity about when alternatives might be more appropriate.

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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