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La Metro

by io.github.pipeworx-io
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Lametro Route Stops

lametro_route_stops
Read-onlyIdempotent

Every stop served by one LA Metro route, in running order, with stop id, name, direction and service day type. AUTHORITATIVE for "which stops does route N serve" and for turning a route into stop ids you can look up with lametro_stop.

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": {
      "route_code": "720",
      "direction_id": 0
    },
    "name": "lametro_route_stops"
  }
}

Input Schema

NameRequiredDescriptionDefault
agencyNo'LACMTA' (bus, default) or 'LACMTA_Rail'.
route_codeYesRoute code from lametro_routes — a number for bus (e.g. "10", "720"), or a line name for rail (e.g. "Metro A-Line").
direction_idNoOptional: keep only direction 0 or 1.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already provide readOnly, openWorld, idempotent, and non-destructive hints. The description adds useful behavioral context by noting the stops are in running order and that service day type is included, but it does not disclose additional traits such as data freshness, pagination, or default behavior when direction_id is omitted.

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?

The description is two sentences with no filler. The core output and ordering are front-loaded, and the second sentence establishes authority and the connection to lametro_stop, earning 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?

For a read-only list tool with a well-documented schema and strong annotations, the description is complete. It names the output fields, ordering, and the route-to-stop workflow. The absence of an output schema is compensated by the description explicitly enumerating what is returned.

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 well documented in the schema. The description refers indirectly to route_code and direction in the output context but does not add new meaning beyond what the schema already provides, so the baseline score of 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 clearly states the tool returns every stop served by one LA Metro route in running order, with specific fields listed. It also declares itself 'AUTHORITATIVE' for a specific question, making its purpose unambiguous and distinct from sibling tools like lametro_routes and lametro_stop.

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 explicitly says when to use this tool: for 'which stops does route N serve' and for converting a route into stop ids for use with lametro_stop. It names the relevant sibling and explains the workflow, but it does not explicitly state when not to use it or exclude alternative scenarios.

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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