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set_train_schedule

Assign a train to a route by specifying stops and wait conditions, then switch it to automatic mode.

Instructions

Set a train's schedule (existing stop names with wait conditions) and switch it to automatic.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stopsYes
train_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses that the tool switches the train to automatic mode, which is a meaningful side effect beyond just setting a schedule. However, it does not mention whether this overwrites an existing schedule, whether it requires the train to be stopped, or what happens to the train's current route.

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

Conciseness4/5

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

The description is a single, front-loaded sentence that conveys the core action and the key side effect. It is concise and every phrase earns its place, though it could add a brief note about overwriting behavior without becoming 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 tool has an output schema and only 2 parameters, so the description doesn't need to explain return values. It covers the main action and the automatic-mode side effect, but for a state-changing tool with no annotations, it should also disclose overwrite behavior and any prerequisites (e.g., train must exist, stops must already be discovered).

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 0%, so the description must compensate. It explains that stops are 'existing stop names (case matters)' and mentions wait conditions, which adds meaning beyond the raw schema. However, it does not explain the wait value format (full/empty/seconds) or the train_id semantics, leaving the agent to infer from the schema.

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 states a specific verb ('Set') and resource ('a train's schedule'), and clarifies that it uses existing stop names with wait conditions and switches the train to automatic. It is clear enough to distinguish from list_trains and other train-related tools, though it doesn't explicitly name a sibling alternative.

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

Usage Guidelines3/5

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

The description implies when to use it: when you want to configure a train's schedule and enable automatic operation. It does not state when not to use it or mention alternatives like list_trains for inspecting schedules, but the context is reasonably clear.

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