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Get Started Free →Guides management of cross-border data transfers under Asia-Pacific regulatory frameworks including APEC CBPR, ASEAN Model Contractual Clauses, Japan APPI supplementary rules, South Korea PIPA provisions, and Thailand/Singapore PDPA mechanisms. Keywords: APEC CBPR, ASEAN MCCs, APPI, PIPA, PDPA, APAC transfers.
.claude/skills/thomasmoreai-apac-transfers/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-11 | ✗→✓ | ▲ Improved | 64% | 0% |
| case-01 | ✓→✓ | = Same ✓ | 69% | 0% |
| case-02 | ✓→✓ | = Same ✓ | 140% | 0% |
| case-03 | ✓→✓ | = Same ✓ | 90% | 0% |
| case-04 | ✓→✓ | = Same ✓ | 53% | 0% |
The Asia-Pacific region encompasses diverse data protection regimes with varying cross-border transfer mechanisms. Unlike the GDPR's unified framework, APAC transfers require navigating multiple overlapping systems: the APEC Cross-Border Privacy Rules (CBPR), ASEAN Model Contractual Clauses (MCCs), and country-specific mechanisms under Japan's APPI, South Korea's PIPA, Thailand's PDPA, and Singapore's PDPA. This skill provides a jurisdiction-by-jurisdiction guide to managing cross-border data flows across the APAC region.
The APEC CBPR system is a voluntary, accountability-based mechanism enabling participating organisations to demonstrate compliance with internationally recognised privacy protections for cross-border data flows within the APEC region.
Participating economies (as of March 2026): Australia, Canada, Japan, South Korea, Mexico, Philippines, Singapore, Chinese Taipei, United States.
Key features:
| Principle | Description | |-----------|-------------| | Preventing Harm | Recognising the interests of the individual regarding the protection of their information | | Notice | Providing clear and easily accessible statements about data practices | | Collection Limitation | Limiting personal information collection to that which is relevant | | Uses of Personal Information | Using personal information only for purposes fulfilling the individual's expectations or as authorised by law | | Choice | Providing individuals with choice regarding collection, use, and disclosure | | Integrity of Personal Information | Maintaining the accuracy, completeness, and currency of personal information | | Security Safeguards | Protecting personal information with appropriate security safeguards | | Access and Correction | Providing individuals with access to their information and the ability to correct inaccurate data | | Accountability | Being accountable for complying with measures that give effect to the principles |
The ASEAN Model Contractual Clauses were adopted by the ASEAN Telecommunications and IT Ministers in 2021 to facilitate cross-border data flows within the ASEAN Economic Community while maintaining data protection standards.
ASEAN Member States: Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, Vietnam.
Key features:
| Section | Content | |---------|---------| | Clause 1 | Definitions aligned with ASEAN Framework on Personal Data Protection | | Clause 2 | Obligations of the data exporter | | Clause 3 | Obligations of the data importer | | Clause 4 | Rights of data subjects | | Clause 5 | Liability and indemnification | | Clause 6 | Governing law and dispute resolution | | Clause 7 | Termination and data return/deletion | | Schedule 1 | Description of transfer (parties, data, purposes) | | Schedule 2 | Technical and organisational measures |
Art. 28 (Cross-Border Transfer):
PPC Supplementary Rules for EU Adequacy:
Athena Global Logistics implementation (Japan operations):
Art. 28-2 (Cross-Border Transfer):
EU-Korea interoperability:
Athena Global Logistics implementation (Korea operations):
Section 28 (Cross-Border Transfer):
PDPC Notification on Adequacy (pending):
Athena Global Logistics implementation (Thailand operations):
Section 26 (Transfer Limitation Obligation):
Mechanisms for compliance:
PDPC enforcement:
Athena Global Logistics implementation (Singapore operations):
| From → To | Japan | South Korea | Thailand | Singapore | Hong Kong | EU/EEA | United States | |-----------|-------|-------------|----------|-----------|-----------|--------|---------------| | Japan | N/A | Consent/Equivalent measures | Consent/Equivalent measures | Consent/Equivalent measures | Consent/Equivalent measures | PPC adequate country | Consent/Equivalent measures | | South Korea | PIPC adequacy | N/A | Consent/Contract | Consent/Contract | Consent/Contract | PIPC adequacy | Consent/Contract | | Thailand | Contract/Consent | Contract/Consent | N/A | Contract/Consent | Contract/Consent | Contract/Consent | Contract/Consent | | Singapore | PDPA contract | PDPA contract | PDPA contract | N/A | PDPA contract | PDPA contract | PDPA contract | | EU/EEA | EU adequacy | EU adequacy | SCCs + TIA | SCCs + TIA | SCCs + TIA | N/A | DPF / SCCs + TIA |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | pass→pass | 14,478 | 8,074 | -44% | 1 | 1 | 0% | 2,336 | 3,956 | +69% | 0 | 0 | — |
case-02 | pass→pass | 9,494 | 9,265 | -2% | 1 | 1 | 0% | 1,759 | 4,215 | +140% | 0 | 0 | — |
case-03 | pass→pass | 12,579 | 11,476 | -9% | 1 | 1 | 0% | 2,337 | 4,447 | +90% | 0 | 0 | — |
case-04 | pass→pass | 13,101 | 5,817 | -56% | 1 | 1 | 0% | 2,354 | 3,600 | +53% | 0 | 0 | — |
case-05 | pass→pass | 10,889 | 4,747 | -56% | 1 | 1 | 0% | 1,969 | 3,368 | +71% | 0 | 0 | — |
case-06 | pass→pass | 7,672 | 4,264 | -44% | 1 | 1 | 0% | 1,423 | 3,297 | +132% | 0 | 0 | — |
case-07 | pass→pass | 13,008 | 15,843 | +22% | 1 | 1 | 0% | 2,262 | 5,164 | +128% | 0 | 0 | — |
case-08 | pass→pass | 11,149 | 10,172 | -9% | 1 | 1 | 0% | 2,050 | 4,474 | +118% | 0 | 0 | — |
case-09 | pass→pass | 13,945 | 11,839 | -15% | 1 | 1 | 0% | 2,584 | 4,600 | +78% | 0 | 0 | — |
case-10 | pass→pass | 7,412 | 5,053 | -32% | 1 | 1 | 0% | 1,288 | 3,482 | +170% | 0 | 0 | — |
case-11 | fail→pass | 13,489 | 8,370 | -38% | 1 | 1 | 0% | 2,490 | 4,083 | +64% | 0 | 0 | — |
case-12 | pass→pass | 13,888 | 10,365 | -25% | 1 | 1 | 0% | 2,633 | 4,465 | +70% | 0 | 0 | — |
case-13 | pass→pass | 10,624 | 11,011 | +4% | 1 | 1 | 0% | 1,904 | 4,569 | +140% | 0 | 0 | — |
case-14 | pass→pass | 11,311 | 7,236 | -36% | 1 | 1 | 0% | 1,924 | 3,750 | +95% | 0 | 0 | — |
case-15 | pass→pass | 12,688 | 8,566 | -32% | 1 | 1 | 0% | 2,200 | 4,094 | +86% | 0 | 0 | — |
case-16 | pass→pass | 5,822 | 4,838 | -17% | 1 | 1 | 0% | 1,133 | 3,421 | +202% | 0 | 0 | — |
case-17 | pass→pass | 8,474 | 7,403 | -13% | 1 | 1 | 0% | 1,433 | 3,658 | +155% | 0 | 0 | — |
case-18 | pass→pass | 18,742 | 17,046 | -9% | 1 | 1 | 0% | 3,029 | 5,496 | +81% | 0 | 0 | — |
case-19 | pass→pass | 9,706 | 8,063 | -17% | 1 | 1 | 0% | 1,444 | 3,836 | +166% | 0 | 0 | — |
case-20 | pass→pass | 14,263 | 14,998 | +5% | 1 | 1 | 0% | 2,315 | 5,150 | +122% | 0 | 0 | — |
case-21 | pass→pass | 5,000 | 3,125 | -38% | 1 | 1 | 0% | 822 | 3,083 | +275% | 0 | 0 | — |
case-22 | pass→pass | 5,986 | 5,595 | -7% | 1 | 1 | 0% | 956 | 3,479 | +264% | 0 | 0 | — |
case-23 | pass→pass | 9,408 | 4,517 | -52% | 1 | 1 | 0% | 1,635 | 3,289 | +101% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +4 percentage points is the difference between those two pass rates over the 23 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.