station_crowd_forecast

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

No annotations are provided, so the description must disclose behavior. It only states 'get forecasted levels' without mentioning mutation, authorization needs, rate limits, data freshness, or output format. This is insufficient for a read operation with no safety indicators.

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 a single concise sentence front-loading key information (verb, resource, interval). No wasted words, but could be improved by clarifying the input scope.

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?

Given no output schema and no annotations, the description should explain that the forecast covers all stations on the specified line or what the output contains. The current description lacks completeness for an effective agent invocation.

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% (the single parameter 'trainLine' has enums and description). The description does not add any additional parameter meaning beyond the schema, achieving the baseline score.

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 clearly states the action 'Get forecasted' and the resource 'MRT/LRT station crowdedness levels', with specific time granularity '30-minute intervals'. It distinguishes from the sibling tool 'station_crowding' which likely provides current crowding. However, it does not clarify that the input is a train line, not a specific station, which may cause slight confusion.

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 guidance on when to use this tool versus alternatives like 'station_crowding' (current) or 'travel_times'. The description does not indicate prerequisites or scenarios where this forecast is appropriate, leaving the agent to infer usage.

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