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get_gdi_trend_analysis

Get trend analysis of the Global Disruption Index over time. Returns the current GDI score plus 7-day, 14-day, and 30-day comparisons with direction, velocity of change, and pillar-level momentum. Identifies which pillar is driving changes and whether risk is accelerating or decelerating. Answers: 'Is supply chain risk getting better or worse, how fast, and why?' Used by supply chain executives for weekly status briefings and by traders to time entry/exit decisions around supply chain volatility.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It transparently describes the return behavior: current score, time-bound comparisons, direction, velocity, pillar-level momentum, and acceleration/deceleration. It discloses the scope (7/14/30-day windows) and the analytical nature (identifies driving pillar). There is no discussion of side effects or permissions, but for a read-only analytics tool this is acceptable. No contradictions with annotations exist.

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 four sentences, each earning its place. It front-loads the primary action, then details the return values, then clarifies the use case. There is no redundant information or fluff, making it appropriately sized and well-structured.

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

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This tool has no parameters, annotations, or output schema, so the description must stand alone. It covers the tool's purpose, the exact data returned (current score, comparisons, direction, velocity, pillar-level momentum), and identifies the driving pillar. It also includes the target audience and use cases. For a simple retrieval tool, this is complete enough.

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 input schema has zero parameters, so the baseline is 4. The description does not add parameter-specific details because none exist. It implicitly indicates the tool requires no inputs by focusing entirely on the output. This is sufficient given the absence of parameters.

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 clearly states the tool 'Get trend analysis of the Global Disruption Index over time' with a specific verb and resource. It further differentiates from siblings by detailing unique outputs (7-day, 14-day, 30-day comparisons, velocity, pillar-level momentum) and the specific question it answers. This distinguishes it from other trend tools like get_port_congestion_trends.

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?

The description provides clear usage context: 'Used by supply chain executives for weekly status briefings and by traders to time entry/exit decisions around supply chain volatility.' It also connects to the specific question 'Is supply chain risk getting better or worse, how fast, and why?' However, it does not explicitly mention alternatives or when not to use this tool, so it lacks explicit 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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool targets a specific and distinct supply chain intelligence need, such as monitoring port congestion, tracking commodity prices, or analyzing trade policy. While there are multiple tools related to signals and ports, each has a clearly defined purpose (e.g., real-time monitoring vs. trend analysis vs. predictive signals), reducing ambiguity.

Naming Consistency3/5

Most tools use the 'get_' prefix (e.g., get_port_congestion_trends, get_border_delays), but several tools lack it, such as commodity_price_monitor, port_congestion_monitor, and supply_chain_risk_assessment. This mix of 'get_' and non-'get_' naming creates inconsistency. Additionally, some names are noun-heavy (risk_pillar_breakdown) while others are verb-noun (commodity_price_monitor).

Tool Count3/5

At 31 tools, the server is on the higher end of acceptable scope for a comprehensive supply chain intelligence platform. However, some redundancy exists (e.g., multiple signal and port tools), and the count may overwhelm agents without clear prioritization. It is slightly above the ideal range for coherence.

Completeness5/5

The tool set covers the major aspects of external supply chain risk: commodities, transportation (ports, borders, air, rail, chokepoints), manufacturing, macroeconomic indicators, trade policy, natural disasters, and labor actions. It also includes analytical tools like trend analysis and predictive signals, leaving no obvious gaps for its stated purpose of monitoring global supply chain disruptions.

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