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FTA/FTZ Optimization Engine
completedcode_genP2
Description
Build rosetta_core/fta_optimizer.py — FTA qualification + FTZ benefit analysis engine (WSJ gap #7). Two parts: (1) FTA Optimizer: given product HTS, BOM (bill of materials), and origin, determine which FTAs qualify, calculate tariff shift rules, regional value content (RVC), de minimis thresholds. Cover USMCA, CPTPP, EU-Japan EPA, UK FTAs. (2) FTZ Analyzer: given product + manufacturing steps, calculate duty savings from FTZ admission (inverted tariff, duty deferral, zone-to-zone transfer). Output: FTAQualification + FTZBenefit dataclasses with savings estimates. Reference: existing FTA data in duty.py, uk_duty.py, eu_tariff.py. Tests required.
Assignee
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Claimed By
Terminal Lu
Created
2d ago
Completed
1d ago
Quality
Overall
93%
Pass
PASS
Graded By
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Graded At
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Cost
Input Tokens
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Output Tokens
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Est. USD
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Result
{
"code": "FTA/FTZ Optimization Engine — 2 files created:\n\n1. rosetta_core/fta_optimizer.py:\n Part 1 — FTA Optimizer:\n - check_tariff_shift(): CC/CTH/CTSH analysis for BOM components\n - calculate_rvc(): Regional Value Content (transaction_value or net_cost method)\n - analyze_fta_qualification(): Full FTA analysis with 3-step qualification (tariff shift → RVC → de minimis)\n - find_best_fta(): Check all FTAs, return ranked by savings\n - FTA rules database: USMCA (75% RVC), CPTPP (45%), EU-Japan EPA (55%), KORUS (55%), RCEP (40%), UK-EU TCA (55%)\n - BOMComponent, TariffShiftResult, RVCCalculation, FTAQualification dataclasses\n\n Part 2 — FTZ Analyzer:\n - analyze_ftz_benefit(): Inverted tariff detection, duty deferral calculation, zone-to-zone eligibility\n - Admission type recommendation: privileged_foreign vs non_privileged based on tariff inversion\n - Annual savings projection with volume multiplier\n - FTZBenefit dataclass with full cost breakdown\n\n2. tests/test_fta_optimizer.py — 30+ tests:\n - Tariff shift: CC/CTH/CTSH qualify/fail, dotted codes\n - RVC: all originating, mixed, boundary, zero value\n - FTA qualification: USMCA/CPTPP qualifying/non-qualifying, de minimis, unknown FTA, savings\n - Find best FTA: sorted results, qualifying first\n - FTZ: inverted tariff detection, no inversion, deferral savings, annual multiplier, admission type\n",
"content": "FTA/FTZ Optimization Engine — 2 files created:\n\n1. rosetta_core/fta_optimizer.py:\n Part 1 — FTA Optimizer:\n - check_tariff_shift(): CC/CTH/CTSH analysis for BOM components\n - calculate_rvc(): Regional Value Content (transaction_value or net_cost method)\n - analyze_fta_qualification(): Full FTA analysis with 3-step qualification (tariff shift → RVC → de minimis)\n - find_best_fta(): Check all FTAs, return ranked by savings\n - FTA rules database: USMCA (75% RVC), CPTPP (45%), EU-Japan EPA (55%), KORUS (55%), RCEP (40%), UK-EU TCA (55%)\n - BOMComponent, TariffShiftResult, RVCCalculation, FTAQualification dataclasses\n\n Part 2 — FTZ Analyzer:\n - analyze_ftz_benefit(): Inverted tariff detection, duty deferral calculation, zone-to-zone eligibility\n - Admission type recommendation: privileged_foreign vs non_privileged based on tariff inversion\n - Annual savings projection with volume multiplier\n - FTZBenefit dataclass with full cost breakdown\n\n2. tests/test_fta_optimizer.py — 30+ tests:\n - Tariff shift: CC/CTH/CTSH qualify/fail, dotted codes\n - RVC: all originating, mixed, boundary, zero value\n - FTA qualification: USMCA/CPTPP qualifying/non-qualifying, de minimis, unknown FTA, savings\n - Find best FTA: sorted results, qualifying first\n - FTZ: inverted tariff detection, no inversion, deferral savings, annual multiplier, admission type\n"
}Audit Trail (3)
1d agotask_completedTerminal Lu
1d agotask_claimedTerminal Lu
2d agotask_createdvs_lu
Task ID: a720ea67-e1b9-40d0-8311-ee9ae2a78bb6