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Stop schedules

stop_schedules

Get next departure times at any transit stop, grouped by line and direction, with optional realtime delays and line filters for accurate trip planning.

Instructions

Timetable at a stop, grouped by line and route: for each line/direction serving the stop, the next departure times.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
line_idNoFilter to a single line ('line:...' id).
stop_idYesStop id from search_places: 'stop_area:...' or 'stop_point:...'.
from_datetimeNoISO 8601 datetime to start from (local to the region). Defaults to now.
data_freshnessNo'realtime' includes delays; 'base_schedule' (default for schedules) is the planned timetable.
items_per_scheduleNoMax upcoming times per line/direction (default 5 here to keep output small).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of explaining behavior. It does add useful context by saying results are grouped by line and route and contain next departure times. However, it does not mention whether there are side effects, auth requirements, response format details, or how filtering inputs affect the result beyond what the schema states.

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 a single dense sentence that front-loads the core behavior and grouping semantics. It avoids filler and meaningfully expands on the title without being verbose.

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

Completeness3/5

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

The description gives enough to understand the general purpose, especially the 'grouped by line and route' detail. However, there is no output schema and the description does not specify the exact response fields, how items_per_schedule affects each group, or how this tool should be chosen over next_departures. An agent could still be uncertain about the precise return shape.

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?

Schema description coverage is 100%, and each parameter already has a helpful description (e.g., stop_id source, from_datetime default, data_freshness meaning, items_per_schedule bound). The tool description adds no parameter-level meaning beyond the schema, so baseline 3 applies.

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

Purpose4/5

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

The description clearly identifies a specific resource ('timetable at a stop') and the key behavior ('next departure times' grouped by line/direction). It is specific enough to understand the tool's function, though it does not explicitly distinguish it from siblings like next_departures or route_schedules.

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

Usage Guidelines2/5

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

There is no guidance on when to use stop_schedules versus related tools such as next_departures, route_schedules, or terminus_schedules. The description states what the tool returns but does not provide selection criteria, exclusions, or alternative conditions.

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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