gapup-mcp

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

Name	Required	Description
`async`	No	If 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.
`route`	No
`companyId`	No	Company registration number or tax identifier
`shipmentId`	No	Unique shipment identifier (e.g., bill of lading number)
`techCategory`	No	Dual-use technology category

Output Schema

TableJSON Schema

Name	Required	Description
`status`	Yes
`matches`	No
`sources`	No
`warnings`	No
`diversionRisk`	No	Calculated diversion risk score (0-100)

TDQS

A3.6/5.0

Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint. Description adds valuable behavioral context: asynchronous execution, cross-referencing specific databases, output with provenance, and timeout prevention hint. 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, efficient and to the point. No unnecessary 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?

Covers purpose, data sources, inputs, output format, and performance constraints. With output schema existing, no need to detail return structure. Missing error handling or edge cases but adequate for a compliance tool.

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 coverage is 80%, so baseline 3. Description lists input types (shipment IDs, company identifiers, geographic routes) that map to parameters, adding some context but not detailed per-parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool detects unauthorized diversion of dual-use technologies and lists data sources. However, it does not explicitly distinguish from similar sibling like 'dual_use_export_risk_mapper', leaving some overlap ambiguity.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. Only mentions async requirement for performance, but no context on preferred use cases or 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

C2.5/5.0

Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

Resources

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