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get_border_delays

Get real-time commercial border crossing wait times at US-Mexico and US-Canada ports of entry. Returns current delay in minutes for commercial vehicles, number of lanes open, and port status. Updated every 30 minutes from US Customs and Border Protection. Covers all major commercial crossings including Laredo, El Paso, Nogales, Otay Mesa, Detroit, Buffalo, and Blaine. Used by logistics companies, freight brokers, and trucking operations to route cross-border shipments through the fastest crossing points.

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

A4.4/5.0
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 discloses the update frequency ('Updated every 30 minutes from US Customs and Border Protection'), the data returned (delay in minutes, lanes open, port status), and coverage scope. This provides useful behavioral context beyond mere 'get data' and helps set expectations, though it omits any error/availability details.

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

Conciseness4/5

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

The description is a compact three-sentence paragraph that front-loads the primary purpose, then adds data details and use cases. It is efficient, but includes a long list of port examples that, while useful, could be trimmed for strict minimalism.

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?

For a simple no-parameter tool with no output schema, the description fully covers what it does, what data it returns, how fresh the data is, geographic scope, and typical use cases. It is complete and self-contained.

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, and the baseline for 0 parameters is 4. Since there is no input schema to clarify, the description doesn't need to explain parameters, but it does adequate context for how the tool is invoked (no arguments needed).

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's function with a specific verb and resource: 'Get real-time commercial border crossing wait times at US-Mexico and US-Canada ports of entry.' It distinguishes this from siblings like port congestion monitors by focusing specifically on border crossing delays and commercial vehicles. This is a precise, distinctive purpose.

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 context for when to use the tool, noting it is 'Used by logistics companies, freight brokers, and trucking operations to route cross-border shipments through the fastest crossing points.' However, it does not explicitly mention when not to use it or compare with alternative sibling tools, so it falls slightly short of a perfect score.

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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