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La Metro

by io.github.pipeworx-io
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Lametro Routes

lametro_routes
Read-onlyIdempotent

Every LA Metro bus or rail route, with its route code, short and long name, direction description and map colour. AUTHORITATIVE for "what routes does LA Metro run" — sourced from LACMTA's own API, not a third-party scrape. Use the returned route_code as input to lametro_route_stops.

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": {
      "agency": "LACMTA",
      "search": "Wilshire"
    },
    "name": "lametro_routes"
  }
}

Input Schema

NameRequiredDescriptionDefault
agencyNo'LACMTA' for bus (default, ~124 routes) or 'LACMTA_Rail' for the rail and busway lines (A/B/C/D/E/K, ~6).
searchNoOptional case-insensitive filter over route name and description (e.g. "Wilshire", "Rapid").

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior, so the bar is lowered. The description adds valuable context on data provenance (LACMTA API, not third-party scrape) and details what route metadata is included, which helps an agent trust and interpret results.

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 sentences, no filler. The first sentence front-loads the resource and fields, the second establishes authority and the downstream workflow. Every sentence earns its place.

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?

Even without an output schema, the description lists the key returned fields, states the full scope of routes, and provides a handoff instruction to the next logical tool. For a simple two-parameter list tool, this is complete.

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 both `agency` and `search` fully described and examples provided. The description itself adds little beyond the schema, aside from linking the returned route_code to lametro_route_stops; that is sufficient but not exceptional.

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 identifies the resource as every LA Metro bus or rail route and lists the returned fields: route code, short/long name, direction description, and map colour. It distinguishes itself from siblings by naming lametro_route_stops as the downstream consumer of the route_code.

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?

It provides clear usage context by labeling the tool AUTHORITATIVE and originating from LACMTA's own API, and it tells the agent to use the returned route_code as input to lametro_route_stops. It does not explicitly enumerate when-not-to-use or alternatives, but the context is strong enough for correct routing.

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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