Query tanker fleet database. Accepts structured filters OR a free-text query (matches vessel name, IMO, owner, or type).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No | Free-text: vessel name, IMO, owner company, or type | |
| search | No | ||
| company | No | ||
| vessel_type | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only states query acceptance modes but omits critical details: what happens when both modes are used simultaneously, pagination behavior (only limit param hints at it), performance implications, or the fact that it is a read-only operation (not explicitly stated).
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, front-loaded with the primary action, and contains no extraneous information. Every word earns its place.
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 5 parameters, no output schema, and no annotations, the description is too sparse. It fails to describe return format, pagination handling, parameter dependencies, or combination rules for structured vs. free-text queries. This leaves the AI agent with significant ambiguity.
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?
With only 20% schema description coverage (only 'query' has a description), the description adds some value by explaining free-text matching targets (vessel name, IMO, owner, type). However, it does not clarify structured filter parameters (search, company, vessel_type) or their interaction, leaving significant gaps.
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 'Query tanker fleet database' with a specific verb and resource, and mentions two modes (structured filters OR free-text query). It is clearly distinguishable from sibling tools like shipping_chokepoint and shipping_emissions.
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 explains the two input modes (structured filters or free-text query) but does not provide guidance on when to use this tool vs. alternatives, nor does it mention prerequisites or exclusions. This is adequate but lacks essential usage context.
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.