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Amtrak

by io.github.pipeworx-io
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Amtrak Station Info

amtrak_station_info
Read-onlyIdempotent

Amtrak station lookup by code or name — station name, 3-letter code, city/state, street address, timezone, coordinates, and how many trains are currently inbound. "Where is the Amtrak station in Denver?", "what is station code NYP". Example: amtrak_station_info({ station: "Denver" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stationYesAmtrak station code (e.g. "DEN", "NYP") or station/city name (e.g. "Denver", "New York")

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "station": "NYP"
+  },
+  {
+    "station": "Denver"
+  }
+]
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds significant behavioral context: it returns station name, code, city/state, address, timezone, coordinates, and inbound train count. 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.

Conciseness5/5

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

Two concise sentences plus an example call. Every sentence adds essential information. Perfectly front-loaded with the tool's purpose.

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

Completeness5/5

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

For a simple lookup tool with one parameter and no output schema, the description fully covers what the tool returns (station name, code, address, etc.) and how to invoke it. No gaps.

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

Parameters4/5

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

The single parameter 'station' is fully described in the schema (station code or city/name). The description reinforces this with concrete examples ('Denver', 'NYP') and query patterns, adding value beyond the schema's property description.

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 specifies the tool performs Amtrak station lookup by code or name and lists the fields returned (station name, code, city/state, address, timezone, coordinates, inbound train count). This clearly distinguishes it from sibling tools like amtrak_station_board or amtrak_train_status.

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

Usage Guidelines4/5

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

The description includes natural language query examples like 'Where is the Amtrak station in Denver?' and 'what is station code NYP', which imply typical usage contexts. However, it does not explicitly state when to use this tool versus alternatives such as amtrak_station_board.

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

All Amtrak toolsInspect
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