stl-transit

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stl_rt_stop_arrivals

Read-onlyIdempotent

Get stop arrivals with realtime predictions merged into the schedule, falling back to scheduled times when realtime data is unavailable.

Instructions

Scheduled departures with realtime predictions merged in -- exactly what the app should render.

When no realtime snapshot is available it degrades to scheduled-only and says so explicitly, which is the behaviour the app must also have.

Args: stop: stop_code or stop_id. at: ISO-8601 instant, America/Chicago if naive. Defaults to now.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`at`	No
`stop`	Yes
`limit`	No
`snapshot`	No
`window_minutes`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 7, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Beyond the readOnly/idempotent annotations, the description discloses that realtime data is merged when available and that the tool explicitly signals when it falls back to scheduled-only. This gives useful behavioral insight for callers.

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 brief and forward-loaded with the core purpose, but includes some redundant phrasing around app behavior ('exactly what the app should render' and 'behaviour the app must also have') that could be trimmed without loss.

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?

While the output schema exists and the description covers the main purpose and an important fallback behavior, it omits context for several input parameters and does not relate the tool to the surrounding workflow (e.g., how it fits with snapshot selection or GTFS departures). This leaves room for user uncertainty.

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

Parameters2/5

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

Schema description coverage is 0%, and the description only explains stop and at. Parameters limit, snapshot, and window_minutes are left completely unexplained, leaving significant ambiguity in how to correctly invoke the tool.

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 returns scheduled departures merged with realtime predictions, which is a specific and unambiguous purpose. It distinguishes this tool from the broader set of GTFS/RT tools by focusing on the app-rendering departure view.

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 mentions a degradation behavior (falls back to scheduled-only) but does not explicitly state when to use this tool versus alternatives like stl_gtfs_departures or stl_rt_decode. It lacks direct 'use this when...' or 'prefer this over...' guidance.

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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