Per-dataset freshness only: pipeline refresh age vs expected cadence, newest record age, source, and status (ok / lagging / stale / empty / unknown). Use before relying on a figure that must be current.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It clearly states the tool is read-only (checking freshness) and describes the output statuses, but does not disclose any edge cases, rate limits, or potential delays in freshness reporting. A score of 3 is appropriate given the sufficient but not exhaustive disclosure.
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 extremely concise with two efficient sentences. The first sentence gives the complete purpose and output format, and the second provides a clear usage guideline. No wasted 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 zero parameters, no output schema, and simple return structure, the description is nearly complete. It explains the output and when to use it. A minor gap is that it does not explicitly state the scope (e.g., which datasets are covered) or any prerequisites, but for a parameterless tool the information provided is largely sufficient.
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 input schema has 0 parameters and the description adds full context on what the tool returns without parameter detail needed. Schema coverage is 100% (no parameters). The description adds meaningful value by explaining the returned fields and status values, which is more than adequate for a parameterless tool.
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 explicitly states the tool's purpose: checking per-dataset freshness metrics such as pipeline age, cadence, newest record age, source, and status (with enumerated statuses). It clearly distinguishes itself from the many sibling tools by focusing on data freshness rather than chokepoints, flows, emissions, or other topics.
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 explicit guidance on when to use the tool: 'Use before relying on a figure that must be current.' This tells the agent exactly the context in which this tool should be invoked, and there are no alternatives to exclude.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes, but there is some overlap between shipping_status and shipping_freshness (both provide freshness information) and between shipping_sanctions and shipping_sanctioned_at_eu (both deal with sanctions, though one is general and the other EU-specific). Descriptions help disambiguate, but the potential for confusion remains.
All tools follow a consistent 'shipping_' prefix followed by a descriptive noun phrase (e.g., shipping_chokepoint, shipping_emissions, shipping_oil_trade). The naming pattern is uniform and predictable, with no mixed conventions.
With 13 tools, the server covers a broad domain (chokepoints, trade flows, emissions, fleet, sanctions, document intelligence, oil data) without being overwhelming. Each tool serves a clear, non-redundant purpose, and the count is well-scoped for a specialized maritime intelligence server.
The tool set covers core maritime intelligence areas: chokepoint monitoring, trade flows, emissions, fleet, sanctions, oil prices, and data freshness. Minor gaps exist (e.g., no tool for port congestion or vessel tracking outside chokepoints), but the core workflows for sanctions, trade, and emissions are well-covered.