SupplyGraph.AI

U.S. Tariff Calculation Agent

tariff_calc

Calculates U.S. customs duties by combining HTS base rates with applicable Chapter 99 measures, providing transparent, rule-based tariff outcomes.

Pricing: {"unit": "credits", "per_run": 10}

Input Schema

TableJSON Schema

Name	Required	Description	Default
`country_or_region`	Yes	Country or region of origin for the imported product, e.g. China, Mexico, European Union.
`product_description`	Yes	Description of the product to import into the United States, e.g. HS code, product name, material, or specifications.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedAug 19, 2026

TDQS

B3.4/5.0

Behavior3/5

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

The annotations include openWorldHint: true, which indicates the tool may perform actions beyond read-only. The description mentions 'transparent, rule-based outcomes' and includes pricing (10 credits per run), which adds some behavior context. But it does not disclose whether it makes external requests, its side effects, or any rate limits. Given the openWorldHint, more transparency is expected.

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 two sentences, front-loaded with the main purpose and a brief note on transparency and pricing. The pricing part is additional but unnecessary for tool invocation; however, it is concise overall. No fluff, but the pricing might be considered irrelevant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With a complex domain (tariffs), output schema exists, and schema covers parameters, the description is adequate but not fully complete. It does not explain the output format, any limitations (e.g., only certain products covered), or prerequisites. The openWorldHint and high complexity suggest more detail on behavior would help.

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?

The input schema covers 100% of parameters with descriptions, so the schema already explains product_description and country_or_region. The description mentions these inputs but does not add much beyond that, not detailing allowed formats or giving examples. Baseline 3 is appropriate since schema does the heavy lifting.

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 it calculates U.S. customs duties by combining HTS base rates with Chapter 99 measures, which is specific and distinguishes it from siblings like tariff_classification. However, it does not explicitly name the sibling tools or compare with them, but the verb 'calculates' and resource 'U.S. customs duties' are clear.

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?

The description implies when to use this tool: when a tariff calculation is needed, listing inputs like product description and origin. It does not explicitly state when not to use it or mention alternatives, but the differentiation from tariff_classification is implicit. Sibling names are not referenced.

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

B3/5.0

Disambiguation3/5

Tools are generally distinct in purpose (search, due diligence, tariff, supply chain), but the two 'search_company_candidates' and 'search_region_candidates' are similar in name and both serve lookup functions, and multiple tools like 'corporate_exception_report' and 'due_diligence_report' overlap in producing comprehensive company reports. The separation is clear enough for an agent but could cause confusion between similar-sounding search tools.

Naming Consistency3/5

Names mix styles: descriptive multi-word names (due_diligence_report, supply_chain_risk_prediction) and abbreviated names (sg_chokepoint, sg_visualization). There is no consistent verb_noun pattern, and the 'sg_' prefix is inconsistently applied. However, most names are readable and roughly follow a noun-based pattern.

Tool Count5/5

With 9 tools, the server covers a broad but coherent domain: search/identity, due diligence, supply chain analysis, and tariff compliance. Each tool addresses a distinct high-level capability, and the count feels appropriate for the scope—not too thin or overly heavy.

Completeness4/5

The tool surface covers major workflows: company identification, due diligence reporting, supply chain risk/chokepoint analysis, tariff classification and calculation. Minor gaps exist (e.g., no explicit update/delete on data since it's a read-only data provider), but for its purpose as an analysis API, it is reasonably complete.

Resources

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