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

Annotations already cover read-only, open-world, idempotent, and non-destructive, so the safety profile is settled. The description adds real context beyond that: the data source (agency GTFS schedule), the presence of live disruption data, and a grounding constraint ('Answer only from this tool's results: never add routes, hours, phone numbers... from memory') that signals authority and completeness limits. The unofficial/non-affiliated disclaimer further sets expectations about data provenance.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

Front-loaded with the resource description, then a compact Args block with examples, then the grounding caveat. No sentence is filler, though the 'never add ... from memory' sentence is more an agent instruction than tool documentation and could be tightened.

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

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

For a two-parameter read tool with no output schema, the description does roughly summarize what comes back (hours, frequency, endpoints, fare, disruptions) and pins down both parameter formats. What is missing is edge-case behavior — unknown agency, no-match or multi-match queries — and any hint of output shape or pagination for a schedule payload that is likely large.

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

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

Schema description coverage is 0% and neither parameter has a description, so the description must carry the burden, and it does: agency is 'slug or name' with four concrete examples including the special 'wmata' Metrorail case, and query is 'route number or name' with examples spanning alphanumeric, named, numeric, and branded routes. It does not say what happens when a query is ambiguous or matches multiple routes, which is the one meaningful semantic gap.

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

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

Names a specific resource and scope: one route from a GTFS schedule, with an explicit field list (service days/hours, typical frequency, endpoints, fare, live disruptions). That is far more than a restatement of "Bus or train route". It does not, however, differentiate itself from sibling get_metro_route or get_fare, and its note that agency "wmata" covers Metrorail lines arguably overlaps with get_metro_route rather than clarifying the boundary.

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

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

There is no when-to-use guidance and no sibling is named as an alternative, even though get_metro_route, get_fare, and get_service_alerts all clearly overlap with the fields this tool returns. Usage is only implied by the returned-field list. The examples clarify invocation, not selection.

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