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

With no annotations, the description carries the full disclosure burden. It helpfully labels itself an '[INFERENCE TOOL]' and publishes the exact IRDI formula, which is real transparency about how the score is computed. It says nothing about data sources, freshness, or update frequency of the underlying delay inputs, which is a meaningful gap for an inference result.

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 purpose and score range are front-loaded in the first sentence, followed by usage triggers, then the formula, then the argument. Everything is compact and each block earns its place; the 'CRITICAL INSTRUCTION FOR LLM' phrasing is loud but not wasteful.

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?

An output schema exists, so return values need not be explained, and the single parameter is documented with examples. The formula is provided so the agent understands the index semantics. The one omission is guidance on valid inputs versus the 'list_supported_ports' sibling, but overall it is sufficient to call the tool correctly.

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 description coverage is 0%, so the description must compensate, and it does: it explains the parameter is a UN/LOCODE and supplies concrete examples ('NLRTM' Rotterdam, 'DEHAM' Hamburg). It also implies the field accepts corridor IDs, not just ports. It does not explain what happens when the default is used, but the coverage is otherwise good.

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 verb ('Calculate') and a named resource ('Intermodal Rail Delay Index (IRDI, 0-100 score)'), so the agent knows exactly what it returns. It is weakened slightly by the presence of the sibling 'get_irdi_index', which computes the same acronym and is never distinguished from this tool.

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?

It gives explicit triggering conditions ('whenever the user asks about INLAND logistics, TRAIN delays, TRUCK bottlenecks, or land-based supply chain issues leaving/entering a port'). However it offers no exclusions and never routes the agent away from the near-identical 'get_irdi_index' sibling, so the when-not case is missing.

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