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mcp-knowledge

by io.github.getgapup

dual_use_tech_diversion_monitor

Read-onlyIdempotent

Asynchronous T5-level tool for COO persona to detect unauthorized diversion of dual-use technologies. Cross-references shipment manifests, EU sanctions lists, and ICAO/IMO transport data to identify suspicious transfers. Inputs: shipment IDs, company identifiers, or geographic routes. Outputs structured diversion risk assessment with source provenance. Requires async:true to avoid 402 timeout.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
routeNo
companyIdNoCompany registration number or tax identifier
shipmentIdNoUnique shipment identifier (e.g., bill of lading number)
techCategoryNoDual-use technology category

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
matchesNo
sourcesNo
warningsNo
diversionRiskNoCalculated diversion risk score (0-100)

TDQS

A4/5.0
Behavior4/5

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

Annotations cover readOnly, openWorld, idempotent. Description adds async behavior, timeout avoidance, and output structure (source provenance). No contradictions.

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?

Three sentences, front-loaded with purpose, each sentence adds value. No fluff.

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?

Covers purpose, data sources, inputs, outputs, async requirement. Minor gap: does not state that at least one input parameter is logically required despite schema making none required. Output schema exists, so return format is covered.

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

Parameters3/5

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

Schema has high coverage (80% according to context, though actual appears higher). Description summarizes input types but adds little beyond schema descriptions. Baseline 3 due to schema richness.

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?

Description clearly states it detects unauthorized diversion of dual-use technologies for COO persona, specifies data sources (shipment manifests, sanctions lists, transport data), inputs, outputs, and async requirement. Differentiates from siblings like dual_use_export_risk_mapper.

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

Usage Guidelines3/5

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

Implied usage context but no explicit guidance on when to use vs alternatives or exclusions. Mentions async requirement but does not compare to similar tools.

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

C2.8/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially in competitive intelligence, ESG, and risk assessment. For example, there are multiple tools for competitor analysis (competitive_deep_dive, competitor_intel, competitor_moves, etc.) with unclear boundaries. Agents would struggle to select the correct tool without deep understanding of subtle differences.

Naming Consistency2/5

Tool names are a mix of English and French, and follow no consistent pattern. Some use snake_case (e.g., abm_architect, action_plan_esg), while others are verb-focused (e.g., content_catalog, fx_rate). The lack of a uniform naming convention makes it hard for agents to predict tool names.

Tool Count1/5

With 271 tools, the server is excessively large. Even for a broad knowledge domain, this number of tools makes discovery and selection inefficient. Typical coherent servers have 3-15 tools; this has an order of magnitude more, indicating poor scoping.

Completeness3/5

The tool set covers many domains (compliance, finance, marketing, HR, etc.), but the coverage is uneven due to redundancy. Key areas have multiple overlapping tools, while some sub-domains may still have gaps. Overall, the surface is broad but not well-curated.

Resources