get_rail_freight_status

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

No annotations are provided, so the description carries full responsibility. It describes the data and sources but does not disclose behavioral details such as update frequency, historical range, or any side effects. The description adds some context (sources and strategic use) but falls short of full transparency.

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 two sentences: the first lists metrics and sources, the second provides usage context and strategic value. It is efficient, front-loaded, and contains no unnecessary words.

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 the tool has no parameters, no output schema, and no annotations, the description covers purpose, data sources, and usage context well. It could be improved by hinting at the return format (e.g., snapshot vs. time series), but overall it is sufficiently complete for a simple tool.

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?

The tool has no parameters and the input schema is empty (100% coverage). There are no parameters to describe, so the description adds no parameter info, but none is needed. Baseline for zero parameters is 4.

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 tool gets US freight rail performance metrics and lists specific indicators (train speed, dwell time, etc.). It distinguishes this tool from siblings by focusing exclusively on rail freight, while siblings cover air cargo, port congestion, and other domains.

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?

The description provides context for when to use the tool: 'When rail slows down, inland supply chains back up within days — this data provides early warning of freight bottlenecks.' It does not explicitly state when not to use or directly compare with sibling tools, but the context is clear enough for selection.

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