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SupplyGraph.AI.Daasmart

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
NameRequiredDescriptionDefault
country_or_regionYesCountry or region of origin for the imported product, e.g. China, Mexico, European Union.
product_descriptionYesDescription of the product to import into the United States, e.g. HS code, product name, material, or specifications.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A3.6/5.0
Behavior3/5

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

The description adds meaningful methodological context by mentioning HTS base rates and Chapter 99 measures, and claims the results are transparent and rule-based. However, with annotations limited to openWorldHint, the description does not disclose important behavioral details such as data mutability, recency of tariff data, unsupported countries, or failure behavior.

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 core functional description is concise and front-loaded in a useful way. The pricing note is relevant operational context, although it could be considered slightly out of place inside the behavioral description. Overall it earns its place with no unnecessary fluff.

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?

Given the 2 required parameters and output schema, the description is mostly sufficient. However, the existence of tariff_classification as a sibling suggests the description would benefit from an explicit cross-reference or workflow hint, especially because product_description can be free-form instead of an exact HS code.

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 description coverage is 100%, and both parameters already have clear descriptions. The tool description does not add any extra interpretation or guidance beyond what the input schema already provides, so it stays at the baseline of acceptable.

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 states a specific action ('Calculates U.S. customs duties') and identifies the exact method ('combining HTS base rates with applicable Chapter 99 measures'). This clearly differentiates the tool from the sibling tariff_classification, which presumably handles classification rather than duty calculation.

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 the intended use: calculating duties for imports into the U.S. However, it does not explicitly explain when to use tariff_calc versus tariff_classification, nor does it address input readiness issues such as the need for an HS code or what to do if the description is too vague to classify or calculate.

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
Disambiguation2/5

大量工具功能高度重叠,例如chain_*和park_*系列均为按不同筛选条件查询企业列表或数量,只是参数不同却拆分为独立工具;enterprise_change_*系列同样针对不同指标逐一拆分。虽然描述清楚各自区别,但代理面对198个工具时极易选错,且许多工具本质应合并为带参数的单一接口。

Naming Consistency3/5

多数工具采用snake_case加领域前缀(如chain_、park_、company_、gov_data_、poi_data_),但存在明显变体如company_certlist、company_randomin_spection(拼写异常)、corporate_exception_report、due_diligence_report、sg_chokepoint等,混用英文抽象名词与动词短语,整体模式可辨认但不统一。

Tool Count1/5

工具总数高达198个,远超合理范围(即使复杂领域也应控制在25个以内)。大量工具是同一逻辑的不同参数变体(如list/num、不同资质条件),完全可以通过参数化减少数量,严重冗余,代理难以有效浏览和选择。

Completeness4/5

工具覆盖领域广泛,包括企业信息、产业链分析、园区统计、地区宏观、POI明细、供应链风险、关税计算等,基本覆盖了商业数据查询的主要需求。虽缺少更新/删除等操作(但作为查询服务器可接受),且部分细分领域可能有遗漏,但整体功能较为完整。

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