SiteCheck Trade & Energy

US import bills of lading for a company: the most recent

logistics_customs_cbp_manifest

Read-only

US import bills of lading for a company: the most recent sea shipments (date, house and master B/L, shipper, origin country, product description, weight, quantity) and the company's top supplier, main origin country and total shipment count, from ImportYeti's public pages built on US Customs (CBP) vessel manifest records. Sea freight into the US only; recent rows only (about 50). Related tools on this server, for a different need: logistics_customs_duty_calc when you need United States import duty lookup from the USITC Harmonized; logistics_customs_broker_verify when you need to check a US customs broker against U.S. Customs and Border. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "company": "<company>"
    },
    "name": "logistics_customs_cbp_manifest"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	Rows to return, 1 to 50 (default 20)
`company`	Yes	US importer name or ImportYeti company slug, e.g. nike usa or nike-usa

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 23, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Beyond the readOnlyHint/openWorldHint annotations, the description discloses provenance (ImportYeti public pages built on CBP records), a hard recency and row ceiling (~50 recent rows), and the billing model ($0.002 USDC per successful call via x402; failed calls uncharged). Cost and data-source disclosure are exactly the kind of behavior an agent cannot infer from structured fields.

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 purpose and scope lead, followed by the return-field inventory, sibling routing and pricing. It is a single dense paragraph with some overlap between title and first clause, but every sentence carries usable information.

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

Completeness5/5

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

For a two-parameter read tool with an output schema, this covers everything an agent needs: what data, from where, how fresh, how many rows, how much it costs, and what to use instead for neighboring needs. Return values are described even though the output schema already carries them.

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%, so both parameters (company, limit) are fully documented in the input schema and the description adds little parameter-level meaning. The field list it gives describes return values, not inputs, so the baseline 3 applies.

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 names the exact resource (US import bills of lading / CBP vessel manifest records), the entity scope (a company), the specific fields returned, and the boundaries (sea freight into the US only, roughly the 50 most recent rows). It also explicitly differentiates itself from logistics_customs_duty_calc and logistics_customs_broker_verify, so an agent can select it without opening a sibling schema.

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

Usage Guidelines4/5

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

It states the clear usage context (recent sea imports for a named company) and routes two adjacent needs to named alternatives. What is missing is an explicit statement of when NOT to use this tool, e.g. for historical or non-US-origin data, so the routing is strong but not exhaustive.

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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