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Cta

by io.github.pipeworx-io
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Cta Train Positions

cta_train_positions
Read-onlyIdempotent

Live Chicago CTA 'L' train positions on one or more lines — where every Red Line, Blue Line, Brown, Green, Orange, Purple, Pink, or Yellow train is right now: lat/lon, heading, next station with ETA, destination, approaching and delayed flags. Answers "where are the Blue Line trains" for the Chicago L. Example: cta_train_positions({ routes: "Red,Blue" })

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "routes": "Red,Blue"
    },
    "name": "cta_train_positions"
  }
}

Input Schema

NameRequiredDescriptionDefault
routesYesComma-separated 'L' lines, full color names accepted: "Red", "Red,Blue", "Brown,Purple"
_apiKeyNoOptional: your own CTA credentials as "train_key:bus_key" — Train Tracker key (free at transitchicago.com/developers) + Bus Tracker key (free at ctabustracker.com)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
-  {
-    "_apiKey": "your-cta-api-key",
-    "routes": "Red,Blue"
-  }
-]New value: +[
+  {
+    "routes": "Red,Blue"
+  }
+]
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-cta-api-key",
+    "routes": "Red,Blue"
+  }
+]
  3. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already disclose read-only, idempotent, and non-destructive behavior, so the bar is lower. The description adds that the data is 'live' and includes approaching/delayed flags, which gives some behavioral context. However, it doesn't mention any rate limits, API key fallback behavior, or data freshness caveats beyond 'live,' so it adds only modest value beyond annotations.

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 front-loads the core purpose and then gives concrete data fields and an example. The list of all eight line names is somewhat redundant with the schema but serves as a quick reference. Overall it is efficient and well-structured, with minimal waste.

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

Completeness4/5

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

Since there is no output schema, the description compensates by enumerating the key return fields (lat/lon, heading, next station ETA, destination, flags). It also clarifies the input format with an example. It doesn't cover edge cases like empty results or API key behavior, but for a simple read-only tool with full parameter documentation, this is sufficient.

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%, so the parameters are already fully documented. The description reinforces the routes parameter by listing the accepted line names and providing an example, but it adds no new semantic detail beyond the schema. Baseline 3 is appropriate.

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 explicitly states it provides live CTA 'L' train positions, enumerates the exact lines covered, and lists the specific data fields (lat/lon, heading, ETA, destination, flags). It also gives a concrete usage example, making the tool's purpose unmistakable and distinct from siblings like cta_train_arrivals or cta_bus_positions.

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 usage by framing the tool as answering 'where are the Blue Line trains' and providing an example call. However, it does not explicitly contrast this with sibling tools like cta_train_arrivals (which gives arrival times) or cta_bus_positions, nor does it state when not to use it. Usage context is present but not explicit enough to earn higher.

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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