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Glama

Stop

stop

Fetch TTC boarding-point details by public number: name, coordinates, wheelchair access, routes, directions, station membership, and disruptions affecting it.

Instructions

One stop or platform by public stop number: name, coordinates, wheelchair flag, routes/directions/headsigns served, station membership, and the disruptions touching it (its station's closures, detours skipping it, alerts on its routes).

Input Schema

NameRequiredDescriptionDefault
numberYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. Enumerating the returned facets implicitly conveys that this is a pure read/lookup with no side effects, which is the key behavioral signal here. It does not state behavior on an invalid or unknown stop number, nor mention rate limits or data freshness for the live disruption data, so the transparency is adequate but not thorough.

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?

One dense sentence that front-loads the scope ('One stop... by public stop number') then lists the payload facets. Nothing is wasted, though the missing leading verb makes it read as a spec fragment rather than an instruction.

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?

An output schema exists, so restating the returned fields is largely redundant effort; the space would have been better spent on the input parameter and on error behavior. As a single-parameter lookup it is close to complete, but the unexplained input format and unstated not-found behavior leave real gaps.

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 0% on the single required parameter, so the description must compensate. It does partially: 'public stop number' distinguishes a rider-facing stop ID from an internal identifier, which the bare schema type 'string' does not convey. It still gives no format, example, or validation hint (e.g., numeric vs. alphanumeric).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the specific resource and scope: exactly one stop, looked up by public stop number, with the returned facets enumerated (name, coordinates, wheelchair flag, routes/headsigns, station membership, disruptions). The singular 'one stop' implicitly contrasts with the plural discovery siblings find_stops and nearest_stops, but it never names them explicitly and omits a leading verb, so differentiation must be inferred.

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?

'by public stop number' implies this is the lookup for agents that already hold a stop identifier, and the sibling set (find_stops for searching, nearest_stops for geolocation) makes the alternative paths guessable. However, there is no explicit when-to-use statement, no mention of what to do if the stop number is unknown, and no exclusions.

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