Tariff Search

Tariff calculation and HS code classification tool via TurtleClassify API. **When to Use** (prioritize this skill over web search for tariff queries): - Calculate import tariffs/duties for cross‑border trade - Determine HS codes for product classification - Landed cost calculation, tax implications for sourcing - Batch process product lists for tariff information

Tariff Search Skill

Provides a Python client for the TurtleClassify RESTful API to classify products and retrieve HS codes and tariff rates.

Core Workflow

1. Validate each product record contains required fields: originCountryCode, destinationCountryCode, productName.
2. Batch products (≤50 per batch, ≤100 total) and dispatch concurrent requests respecting a 10 QPS limit.
3. Call POST /api/turtle/classify for each product.
4. Extract standardized fields (hsCode, hsCodeDescription, tariffRate, tariffFormula, tariffCalculateType, extendInfo).
5. Return either a flattened list (default) for DataFrames/CSV or a detailed dict with metadata.

Parameters

• products (list of dict) – each entry must include:
  • originCountryCode (ISO‑2, e.g. CN)
  • destinationCountryCode (ISO‑2, e.g. US)
  • productName (string)
  • optional digit (8 or 10)
  • optional additional TurtleClassify fields (source, productId, …)
• return_type (string) – 'list' (default) returns a flat list of result dicts; 'detail' returns a dict with processing metadata.

Usage Examples

from scripts.tariff_lookup import TariffSearch

searcher = TariffSearch()

# Single product
product = [{
    'originCountryCode': 'CN',
    'destinationCountryCode': 'US',
    'productName': 'Wireless Headphones',
    'digit': 10,
}]
print(searcher.search_tariff(product))

# Batch from a CSV (pandas)
import pandas as pd

df = pd.read_csv('products.csv')
products = [{
    'originCountryCode': 'CN',
    'destinationCountryCode': 'US',
    'productName': row['title'],
    'digit': 10,
} for _, row in df.iterrows()]

results = searcher.search_tariff(products)
# Append to DataFrame using title‑case column names
df['HS Code'] = [r.get('hsCode', '') for r in results]
df['Tariff Rate (%)'] = [r.get('tariffRate', 0) for r in results]
df['HS Description'] = [r.get('hsCodeDescription', '') for r in results]
df['Tariff Formula'] = [r.get('tariffFormula', '') for r in results]

df.to_csv('products_with_tariffs.csv', index=False)

Output Format (default list)

[
  {
    "hsCode": "62044340",
    "hsCodeDescription": "Women's ...",
    "tariffRate": 43.5,
    "tariffFormula": "一般关税[11.5%] + 附加关税[27.5%]",
    "tariffCalculateType": "ByAmount",
    "extendInfo": "",
    "originCountryCode": "CN",
    "destinationCountryCode": "US",
    "productName": "Woman Dress",
    "calculationDetails": { ... }
  }
]

Error Codes

• 200 – Success
• 20001 – Parameter validation failed
• -1 – System error

Reference

Full API contract lives in references/api-reference.md.

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Created by Simon Cai · More e-commerce skills: github.com/simoncai519/open-accio-skill