List Transit Vehicle Positions

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

Annotations already signal read-only, idempotent, and open-world behavior. The description adds valuable, non-obvious behavioral details: coordinates arrive as strings and may be empty, agencies with no real-time feed return nothing (with a pointer to check 'Monitored'), and a 60-requests-per-hour rate limit. This goes well beyond the annotations and prepares the agent for realistic edge cases.

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?

The description is longer than strictly necessary because it repeats the Args and Returns sections that already exist in the schema. However, it is well-structured with clear sections (purpose, args, returns, examples, error handling) and the most important guidance (purpose and alternative) is front-loaded. Every section adds unique value (examples, error handling, rate limits), so the length is justified despite some redundancy.

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 list tool with an output schema and read-only annotations, the description covers all essential context: proper use cases, alternatives, parameter semantics, edge cases (missing coordinates, empty feeds, rate limits), and concrete examples. Nothing an agent needs to call it correctly is missing.

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 coverage is 100%, so the schema fully documents each parameter. The description adds some meaning beyond that: it clarifies that 'line' matches on name or id, and provides concrete examples (operator_id='SF', line='N') that illustrate how parameters map to real queries. Defaults for limit and response_format are repeated, but the examples and matching detail provide modest added value.

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?

The description opens with a clear, specific statement of what the tool does: 'Live positions of an agency's vehicles currently in service.' It names the resource (vehicles) and action (list positions), and explicitly differentiates from a sibling tool ('For "when does one get to me", use transit_next_departures instead'), so an agent can distinguish it without opening schemas.

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?

Provides explicit when-to-use guidance: answers 'where are the trains right now' and 'how many buses are running on this line', and gives a direct exclusion: 'Don't use when: you want arrival times at a stop' with the alternative named. Examples reinforce correct usage and operator/line selection.

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