Sydney return-to-office (Opal)

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

No annotations are provided, so the description carries the full behavioral burden. It usefully defines the semantics and units of each measure ('1.0 = no gap', shares of Tue-Thu, tap-ons per day), but says nothing about return format, pagination, data freshness, or rate limits.

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?

A single dense paragraph where every clause carries information about a distinct measure; the core measure (friday_gap) is front-loaded before the secondary views. No filler.

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?

With no output schema, the description should characterize the returned data. It explains units and the 1.0 baseline for the gap measures but never describes the response shape, series structure, or how the six views differ in their output format.

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 75% and the 'view' enum has no per-value descriptions in the schema, so the description's detailed gloss on each of the six view values (friday_gap, monday_gap, evening_volume, baseline, cbd_hourly, suburban_morning) adds real meaning. It also confirms the Sydney CBD default that the schema only implies.

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 states a specific resource and source: TfNSW Opal tap data measuring how Sydney commutes since COVID. It clearly separates itself from the RBA/ABS siblings in a different domain, though it never states the verb explicitly or that it returns a time series.

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?

No explicit when-to-use or when-not-to-use guidance, and no named alternatives. Usage is only implied through the explanation of each view, which does help an agent pick the relevant measure (e.g. friday_gap for return-to-office) but leaves the choice unstated.

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