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sg_mrt_crowd

Check real-time or forecast crowd density for Singapore MRT/LRT lines. Select a train line to view station-level crowding conditions.

Instructions

Get MRT/LRT station crowd density (real-time or forecast). Requires SG_LTA_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lineYesTrain line code: NSL, EWL, NEL, CCL, DTL, TEL, BPL, SLRT, PLRT
forecastNoIf true, get forecast instead of real-time
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only mentions the SG_LTA_KEY requirement, which is a prerequisite rather than a behavior. It does not state whether the operation is read-only, discuss rate limits, error conditions, or output format. The read-only nature is only implied by 'Get'.

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?

The description is a single, clear, and direct sentence that front-loads the main action. It is concise with no unnecessary information, though it could be slightly more structured if it included additional behavioral context.

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

Completeness2/5

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 explain what the response contains or how to interpret the crowd density data. It does not. The description is too minimal to fully prepare an agent for using the tool correctly, leaving gaps in expected output and possible failure modes.

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 coverage is 100% with both parameters fully described. The description's mention of 'real-time or forecast' only echoes the existing 'forecast' parameter description. No additional parameter semantics are provided beyond the schema.

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

Purpose5/5

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

The description clearly states 'Get MRT/LRT station crowd density' with a specific verb and resource. It also specifies real-time or forecast, which further distinguishes it from sibling tools like sg_train_alerts or sg_bus_arrival.

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

Usage Guidelines4/5

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

The description clearly implies when to use this tool (when crowd density is needed), and the context is obvious from the name and description. However, it does not explicitly name alternatives or exclusion conditions, so it stops short of a 5.

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

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