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get_port_congestion_trends

Get port congestion trend analysis — not just current congestion, but direction and trajectory. Returns how congestion has changed relative to historical baselines, identifies ports where congestion is accelerating, and flags ports approaching critical thresholds. Answers: 'Which ports are getting worse and how fast?' Used by logistics planners to reroute shipments before congestion peaks, and by importers to anticipate lead time extensions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.4/5.0
Behavior4/5

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

Given no annotations, the description carries the full burden and does well by disclosing concrete behavioral aspects: comparison to historical baselines, detection of accelerating congestion, and flagging of critical thresholds. It doesn't mention data freshness or limitations, but for a read-only analysis tool this is acceptable.

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

Conciseness5/5

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

The description is concise and front-loaded with the core purpose. Every sentence earns its place: the first establishes the focus, the second details the outputs, the third answers a clarifying question, and the fourth lists use cases. No wasted words.

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?

For a zero-param, no-output-schema tool, the description gives a complete picture of what the tool returns and who should use it. It lacks specifics like time horizon or update cadence, but these are not essential for selection among siblings, and the differentiation from current congestion tools is clear.

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?

The tool has zero parameters, so the input schema provides no semantic information. The description adds meaning about the analysis dimensions (trend, trajectory, historical baseline) without needing to explain inputs. Baseline for 0 params is 4.

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?

The description uses a specific verb 'Get' and resource 'port congestion trend analysis', and clearly differentiates from sibling tools by emphasizing 'not just current congestion, but direction and trajectory.' It answers a concrete question ('Which ports are getting worse and how fast?') and describes the unique analytical value.

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?

It provides clear use cases for logistics planners and importers, and implicitly contrasts with current-congestion monitoring ('not just current congestion'). However, it does not explicitly name an alternative tool or state when not to use it, so it stops short of full guidance.

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

A4/5.0
Disambiguation4/5

Most tools have distinct purposes targeting specific supply chain dimensions like commodity prices, port congestion, or manufacturing indicators, with clear boundaries. However, some overlap exists between tools like 'get_commodity_volatility_alerts' and 'commodity_price_monitor', which both focus on commodity price changes, potentially causing confusion in tool selection.

Naming Consistency4/5

Tool names follow a consistent 'verb_noun' pattern (e.g., 'get_action_signals', 'get_air_cargo_disruptions'), with minor deviations like 'commodity_price_monitor' and 'manufacturing_output_indicator' using noun-based naming. This maintains readability but slightly breaks the overall convention.

Tool Count2/5

With 25 tools, the count feels excessive for a single server, likely overwhelming users and agents. The server covers a broad domain, but many tools could be consolidated (e.g., multiple commodity-related tools) to reduce complexity and improve focus.

Completeness5/5

The tool set provides comprehensive coverage of the supply chain domain, including risk assessment, real-time monitoring, predictive analytics, and executive reporting. It supports full lifecycle management from data retrieval to actionable insights, with no obvious gaps in functionality.

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