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supply-chain-intelligence

by io.github.SupplyMaven-SCR

get_supply_chain_weekly_brief

Comprehensive weekly supply chain situation report combining all SupplyMaven data sources into an executive-level brief. Includes GDI score with pillar breakdown and trend, top disruption events with risk scores, manufacturing output status across 8 regions, commodity price movements, port congestion highlights, and active predictive signals. Designed to answer 'what happened this week in supply chains?' in a single call. Used by executives, procurement leaders, and supply chain managers for weekly risk reviews and stakeholder briefings.

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

A4.1/5.0
Behavior3/5

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

With no annotations, the description carries full burden. It discloses the report's contents (GDI, disruptions, manufacturing, etc.) and its aggregation behavior, but says nothing about data freshness, whether it triggers on-demand computation, or potential side effects. Since it's a getter with no parameters, this is acceptable but not fully transparent.

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 three sentences with the main purpose front-loaded: 'Comprehensive weekly supply chain situation report.' It efficiently enumerates contents and target users. Minor redundancy exists between 'executive-level brief' and 'Used by executives', but overall it is well-structured and waste-free.

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?

Given there is no output schema and no parameters, the description is the sole documentation. It enumerates six key sections of the report, which is comprehensive for an executive brief. It does not describe the response structure or data sources, but the high-level nature of the tool makes this adequate.

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 0 parameters, so the baseline is 4. The description adds value by detailing the report's sections (pillar breakdown, risk scores, regional manufacturing, etc.), which helps the agent understand what the returned brief includes, even though no parameters need explanation.

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 is specific: it produces a 'comprehensive weekly supply chain situation report' combining all data sources. It clearly distinguishes itself from sibling tools like get_gdi_trend_analysis or get_port_congestion_trends by offering a single-call executive summary, making its purpose unambiguous.

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 explicitly states it 'Designed to answer what happened this week in supply chains?' and is used for 'weekly risk reviews and stakeholder briefings', which clearly implies usage for high-level overviews. While it doesn't explicitly exclude alternative tools, its positioning as a one-stop brief makes the intended context clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All supply-chain-intelligence toolsInspect
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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.

Resources