gapup-mcp

africa_trade_preference_arbitrage

Read-onlyIdempotent

Analyzes AGOA (African Growth and Opportunity Act) and EBA (Everything But Arms) trade preference arbitrage opportunities for COOs evaluating export strategies. Compares tariff rates, trade volumes, and preference utilization across eligible African countries using WITS and OECD trade data. Returns structured analysis of potential duty savings, market access advantages, and compliance requirements. — pass async:true REQUIRED to avoid x402 timeout.

Input Schema

TableJSON Schema

Name	Required	Description
`year`	No	Reference year for trade data
`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.
`hs_code`	Yes	6-10 digit Harmonized System product code
`exporting_country`	Yes	ISO 2-letter country code of African exporter
`importing_country`	No	ISO 2-letter country code of target market (US/EU)
`preference_scheme`	No	Trade preference scheme to analyze

Output Schema

TableJSON Schema

Name	Required	Description
`status`	Yes
`sources`	No
`warnings`	No
`duty_savings_pct`	No	Estimated duty savings percentage under preference scheme
`trade_volume_usd`	No	Annual trade volume in USD for given HS code
`market_access_score`	No	Composite score of market access advantage (0-100)
`compliance_requirements`	No	List of compliance requirements for preference eligibility
`preference_utilization_rate`	No	Percentage of eligible exports utilizing preference

TDQS

A3.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint. The description adds valuable behavioral context: it uses WITS and OECD data, returns structured analysis, and crucially warns about the async parameter to avoid timeouts. This exceeds annotation coverage.

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?

Four sentences with no redundancy: purpose, details, output, critical usage note. Could be slightly more structured (e.g., bullet points) but efficient overall.

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 6 parameters and an output schema, the description covers purpose, data sources, output nature, and a critical usage note. It doesn't explain the output schema, but since one exists, the burden is lower. Largely complete.

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 100% with descriptions for all 6 parameters. The description adds no extra meaning beyond what schema provides, except the async timeout note which is already in the parameter description. Baseline 3 is appropriate.

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?

The description clearly states the tool analyzes AGOA/EBA trade preference arbitrage opportunities for COOs, comparing tariff rates, trade volumes, etc. It distinguishes from siblings like 'africa_trade_preference_optimizer' only implicitly; explicit differentiation is missing.

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?

The description targets 'COOs evaluating export strategies' but provides no guidance on when to use this tool versus alternatives (e.g., 'agoa_eba_intelligence' or 'tariff_arbitrage_finder'). No exclusions or context for siblings.

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.

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