Get weather forecast for bus travel destinations. Provides detailed weather predictions including temperature, precipitation, and road conditions to help plan bus journeys safely.
| Name | Required | Description | Default |
|---|---|---|---|
| end_date | No | End date for forecast in YYYY-MM-DD format (optional) | |
| location | Yes | City name for weather forecast (e.g., 'İstanbul', 'Ankara') | |
| start_date | Yes | Start date for forecast in YYYY-MM-DD format |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this as a read-only, non-destructive operation. The description adds useful context about the forecast contents, such as temperature, precipitation, and road conditions, but does not disclose operational details like units, forecast range, or data limitations. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no wasted words. The main purpose is front-loaded, and the second sentence adds relevant detail about what the forecast includes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 3-parameter read-only forecast tool with a fully documented schema and useful annotations, the description is largely complete. It states the purpose and the key output contents. A minor gap is the lack of detail on units or exact response structure, but this is not critical for selecting and invoking this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents location, start_date, and end_date. The description adds no parameter-specific semantics beyond general forecast content, which is acceptable given the schema's thoroughness.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific action, 'Get weather forecast', and clearly identifies the resource as 'bus travel destinations'. It also signals differentiation from sibling tools such as car_weather_forecast, flight_weather_forecast, and hotel_weather_forecast by emphasizing 'bus journeys' and 'road conditions'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for planning bus journeys safely, which gives some context. However, it does not explicitly state when to prefer this tool over the sibling weather forecast tools, nor does it mention exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct combination of travel vertical (flight, bus, car, hotel) and action (search, allocate, weather, room details). The weather forecast tools are separated by transport mode with different condition types, so an agent can reliably choose the right one.
Most tools follow a clear resource_action pattern such as bus_search, flight_allocate, and hotel_weather_forecast. Minor deviations are hotel_room_detail, which uses a noun phrase, and mcp_enuygun_ping, which breaks the pattern but is a standard connectivity check.
Twelve tools is a reasonable size for a multi-vertical travel booking server covering flights, buses, cars, hotels, and weather. Each vertical has search and weather coverage, with allocation and detail tools where most relevant.
Flight and car searches have matching allocation tools, but bus_search has no bus allocation/booking tool and hotel_search/hotel_room_detail have no hotel booking allocation tool. The core search and planning surface is present, but the booking lifecycle is inconsistent across verticals.
