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nhannpl

Winnipeg City MCP Server

by nhannpl

find_stops_near

Find bus stops near specific coordinates in Winnipeg to get stop IDs for trip planning. Search within a configurable distance up to 2000 meters.

Instructions

Search for bus stops near a specific geographic coordinate.
Useful when you know the location (e.g. from a user's known lat/lon) but need stop IDs.

NOTE: Distance is capped at 2000 meters to allow efficient querying.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYes
lonYes
distance_metersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Since no annotations are provided, the description carries the full burden. It discloses key behavioral traits: the distance cap ('Distance is capped at 2000 meters') and efficiency consideration ('to allow efficient querying'). However, it does not mention other potential behaviors like rate limits, authentication needs, or error handling, which could be relevant for a search tool.

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 appropriately sized and front-loaded, with the core purpose stated first, followed by usage context and a behavioral note. Each sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.

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

Completeness4/5

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

Given the tool's moderate complexity (3 parameters, no annotations, but with an output schema), the description is mostly complete. It covers purpose, usage, and a key behavioral constraint. Since an output schema exists, it need not explain return values, but it could benefit from mentioning prerequisites (e.g., coordinate format) or error cases to be fully comprehensive.

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

Parameters4/5

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

With schema description coverage at 0%, the description must compensate. It adds meaning by explaining that parameters are for 'a specific geographic coordinate' and that distance is 'capped at 2000 meters,' which clarifies the purpose of lat, lon, and distance_meters beyond their schema titles. However, it does not detail the units or constraints for lat/lon (e.g., valid ranges) or the default value for distance_meters.

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: 'Search for bus stops near a specific geographic coordinate.' It specifies the verb ('Search'), resource ('bus stops'), and context ('near a specific geographic coordinate'), distinguishing it from siblings like get_bus_arrivals or plan_journey. The additional note about obtaining stop IDs further clarifies the output intent.

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 clear context for when to use this tool: 'Useful when you know the location (e.g. from a user's known lat/lon) but need stop IDs.' However, it does not explicitly state when not to use it or name alternatives among the sibling tools, such as using plan_trip for route planning instead.

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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