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mbta_get_track_prediction

Predict which track a train will use at a station by inputting trip ID, route, station, and scheduled time.

Instructions

Get track prediction for a specific trip using IMT API. Predicts which track a train will use at a station.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
station_idYesStation ID where prediction is needed
route_idYesRoute ID (e.g., CR-Providence)
trip_idYesTrip ID for the specific train
headsignYesDestination/headsign (e.g., South Station)
direction_idYesDirection (0 or 1)
scheduled_timeYesScheduled departure/arrival time (ISO format)
Behavior2/5

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

No annotations provided, so the description carries full burden. It only mentions 'predicts' without disclosing if it is real-time, data freshness, or potential errors.

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?

Two sentences and 15 words is concise, but the second sentence is largely redundant with the first, reducing efficiency.

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

Completeness2/5

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

With 6 required parameters and no output schema, the description is too brief, lacking details on return values or error handling.

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 coverage is 100% with good parameter descriptions. The tool description adds no extra meaning beyond the schema, which is acceptable per baseline.

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 states it gets a track prediction for a specific trip, distinguishing it from general predictions. However, it does not differentiate from the sibling 'mbta_get_chained_track_predictions'.

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?

No guidance on when to use this tool versus alternatives such as mbta_get_predictions or mbta_get_chained_track_predictions.

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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