shipping_oil_prices
Get oil price benchmarks (WTI, Brent)
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| benchmark | No | all |
maritime
TDQS
C2.5/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behavior. It only states 'Get oil price benchmarks' without revealing whether it's read-only, rate limits, or data freshness constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise at one sentence, but it sacrifices critical information about parameters and usage, making it under-specified rather than efficiently concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, no annotation, and no parameter descriptions, the description fails to provide a complete picture. It leaves significant gaps for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, yet the description does not mention the parameters 'days' or 'benchmark' or explain their meaning. The agent has no clue what these parameters do.
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?
Clearly states the tool retrieves oil price benchmarks and names specific examples (WTI, Brent). The sibling tools cover different aspects of shipping, so this tool is well-distinguished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, no prerequisites or when-not-to-use context provided.
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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TDQS
A3.6/5.0
Disambiguation4/5
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.
Naming Consistency5/5
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.
Tool Count5/5
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.
Completeness4/5
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.