Aether-X Port Delay Intelligence

get_port_operations_status

[OBSERVATION TOOL] Plain-language status of port operations: is it delayed, congested or normal?

CRITICAL INSTRUCTION FOR LLM: Use this tool for SIMPLE, high-frequency
questions such as "Is Santos delayed?", "How many ships are waiting a
Paranaguá?", "What is the ETA delay risk at this port?", "Where is my cargo
stuck?". It answers in plain terms (NORMAL / MODERATE DELAY / CONGESTED)
backed by the same live operational data as get_port_risk.

This tool is FREE (observation layer). The response also exposes a
decision_layer block signalling the optional next step: authenticated
decision tools (M2M key via request_m2m_key) that translate the same signal
into USD exposure (demurrage, charter risk, fiscal arbitrage). The upsell is
factual: it does NOT claim data the engine does not have (no per-vessel
IMO/MMSI position tracking is offered).

Args:
    port_id: UN/LOCODE e.g. "BRSSZ" (Santos), "BRPNG" (Paranaguá), "NLRTM" (Rotterdam).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`port_id`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedSep 29, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does so well: it discloses the cost model ('FREE, observation layer'), the response shape (plain terms plus a decision_layer block), and an honest limitation ('no per-vessel IMO/MMSI position tracking is offered'). It stops short of describing rate limits or failure behavior, but for an observation tool this is a rich disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core purpose is front-loaded and the sections are scannable, but the middle block leans promotional ('The upsell is factual') and spends several sentences justifying the decision-layer monetization rather than helping the agent invoke the tool. That material is informative but not tightly earned.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

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 spelled out, and the single required parameter is fully specified with format and examples. With no annotations, the description supplies the behavioral context itself. Nothing essential for correct invocation is missing, though pagination or latency characteristics are absent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the schema itself only says 'Port Id' as a string, so the description must compensate — and it does, specifying the UN/LOCODE format with three worked examples ('BRSSZ' Santos, 'BRPNG' Paranaguá, 'NLRTM' Rotterdam). This is exactly the syntax an agent needs to construct a valid call.

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?

States a specific verb and resource ('Plain-language status of port operations') and immediately names the outcome vocabulary (NORMAL / MODERATE DELAY / CONGESTED). It also positions itself against the sibling get_port_risk ('backed by the same live operational data as get_port_risk'), so an agent can distinguish the observation layer from the risk-scoring tool without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit triggering conditions with concrete example questions ('Is Santos delayed?', 'Where is my cargo stuck?') and routes heavier dollar-exposure questions toward authenticated decision tools. The only gap is that it never states a hard 'do not use for X' exclusion; the alternative routing is implied through the upsell framing rather than declared as exclusions.

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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